MATHEMATICAL MODELING OF
research grant
111-00539
Johns Hopkins
Uniuersity
-------
-------
MATHEMATICAL MODELING
OF SOLID WASTE COLLECTION POLICIES
Volumes 1 and 2
This final report (SW-lrg) on work performed under
Research Grant No. UI-00539 to the Johns Hopkins University
was written by MARCUS M. TRUITT, JON C. LIEBMAN, and CORNELIUS W. KRUSE
and has been reproduced as received from the grantee.
Environmental P-— -•- +•
Library, L " V^?Ctl
1 North'vfoo^i.'••-»<>
Chicago, IllinoisV60606
U.S. DEPARTMENT OF HEALTH, EDUCATION, AND WELFARE
Public Health Service
Environmental Health Service
Bureau of Solid Waste Management
1970
-------
Public Health Service Publication No. 2030
ENVIRONMENTAL FKCIUCTICN AGEi«v-
For sale by the Superintendent of Documents, U.S. Government Printing Office
Washington, D.C., 20402 - Price $2.25
-------
FOREWORD
THE OBJECTIVE of the Bureau of Solid Waste Management is to aid in
developing economic and efficient solid waste management practices.
As authorized under the Solid Waste Disposal Act (Public Law 89-272),
the Bureau has made almost 100 solid waste research grants to non-
profit institutions in this effort to stimulate and accelerate the
— development of new or improved ways for handling the Nation's
^y discarded solids. The present document reports on work completed
under one of these research grants. Received in two volumes from
the grantee, the report is published herein as a single book; other
^ than a new cover, title page, and this foreword, the report is
! reproduced exactly as received from the grantee.
^y
i
f"- To predict results of proposed changes in an existing municipal
fv,.
*-. solid wastes collection system, mathematical simulation models were
or)
i**" devised by the grantee. Such models, as described in the first
^ volume of this report, would be applicable for comparing costs of
collection in other locations. The second volume is a guide that
shows how the models can be used as an aid to decision making for
solid waste management.
The models were tested successfully by the grantee to predict the
results of changes in the study system, thereby verifying promising
applicability to other systems. We hope that the mathematical models,
as well as the information given on their use, will be helpful to
those who must develop, fund, and operate efficient waste collection
systems.
--RICHARD D. VAUGHAN, Director
Bureau of Solid Waste Management
111
-------
-------
VOLUME
-------
-------
ABSTRACT
Extensive observation was made of refuse collection in urban residential
areas in the city of Baltimore and its environs. All data were collected
in the context of a classification of four neighborhood types of household
densities.
Three models were prepared in FORTRAN IV for simulation of refuse
collection systems on an IBM 7094 computer. Data within the models
can be easily changed so as to allow other cities' system characteristics
to be substituted for the Baltimore data .
Model 1
Model 1 simulated many trucks collecting in an urban neighborhood which
had household densities per acre defined within certain limits. Model
response of major interest was the number of household units which could
be serviced by a collection truck in an eight hour day. Runs were made
for different combinations of haul distances, neighborhood densities,
collection frequencies, sizes of trucks, and seasons.
Model 2
Model 2 was similar to Model 1 with one major policy difference between
the two models: Model 2 policy assigns a definite number of households to
Vll
-------
each truck as the day's task; completion of the task is the operational
policy rather than working an eight hour day. Response of major interest
is unit cost of the operation for combinations of different collection fre-
quencies, neighborhood types, and haul distances. Sensitivity of response
was noted for changes in size of daily task assignment.
Model 3
Model 3 simulates a more complex, more realistic system operating under
an assigned task policy in a large urban area of many residential subareas,
each definable in one of the four household density classifications.
As initial action, Model 3 calculates the number of daily routes in each
subarea; this is a function of subarea neighborhood type, collection fre-
quency, and haul distance. It then assigns trucks by number to subareas
by days of the week .
It then simulates collection for a six-day week in the entire area and
prints a resume of the week's activities. The model is structured for
semiweekly or triweekly collection frequencies, and can simulate a
system with or without a transfer station. Different locations for final
disposal sites or transfer stations can be cost investigated and so compared .
Vlll
-------
Many runs were made in this study with the northwest quadrant of Baltimore
as the area for which the collection activity was simulated. The response
of major interest was always unit cost in dollars per ton for the many com-
binations of policies and affecting variables.
Specific Results
A refuse collection simulation model, Model 3, was built which has the
potential to operate realistically under most system policies and urban
environmental conditions. Runs with this model indicated:
I . An increase in collection frequency from semiweekly to triweekly in
the northwest quadrant of Baltimore would increase costs approximately
Sl:00 per ton.
2. In this northwest Baltimore area, eight miles is critical haul distance
above which a transfer station is justified.
IX
-------
-------
TABLE OF CONTENTS
Page
Chapter 1 Introduction 1
Chapter 2 A Survey of Pertinent Literature 13
Chapter 3 The Policies and Structures of Models 1 and 2 25
Chapter 4 Results from Models I and 2 50
Chapter 5 The Policies and Structure of Model 3 76
Chapter 6 Results from Model 3 1 15
Chapter 7 Conclusions and Summary 135
Appendix A Data from the City of Baltimore 153
Appendix B Data other than Baltimore 185
Appendix C Data Gathering Forms 190
Appendix D Cost Calculations for Semiweekly and
Triweekly Collection, Chapter 4 192
Appendix E Results from Model 3 204
Bibliography 217
XI
-------
TABLE OF ILLUSTRATIONS
Number
3-1
3-2
3-3
3-4
3-5
3-6
3-7
3-8
4-1
4-2
4-3
4-4
4-5
4-6
4-7
Title
General Schematic of Models 1 and 2
Interaction of Model 1 and 2 Subroutines
Logic Flow of DATMAK Subroutine
Logic Flow of TRAFIC Subroutine
Logic Flow of COLECT Subrout ine. Model 1
Logic Flow of COLECT Subroutine, Model 2
Logic Flow of CINERA Subroutine, Model 1
Logic Flow of CINERA Subroutine, Model 2
Household Units Serviced Daily
Gross Acres Serviced Daily
Sensitivity of Model 2 Results to Random
Number Sequences
Sensitivity of Model 2 Results to Seasonal Effects
Collection Costs for Semiweekly Collections
Collection Costs for Triweekly Collections
Summary of Collection Costs by Neighborhood
Page
34
35
43
44
45
46
47
48
53
55
57
59
63
63
Types 64
4-8 Summary of Costs of Semiweekly and Triweekly
Collection 65
4-9 Percentage of Time Spent in Different Crew
Activities 70
XI1
-------
TABLE OF ILLUSTRATIONS (cont.)
Number Title Page
4-10 Variance of Unit Costs with Size of Daily
Task Assignment 74
4-11 Number of Trucks on Overtime versus Daily
Task Assignment 75
5-i General Schematic of Model 3 91
5-2 Interaction of Model 3 Subroutines 94
5-3 Logic of TRAFIC Subroutine, Model 3 101
5-4 Logic of COLECT Subroutine, Model 3 102
5-5 Logic of DSPOSL Subroutine, Model 3 103
5-6 Logic of RIGOUT Subroutine, Model 3 106
5-7 Logic of RIGBAK Subroutine, Model 3 107
6-1 Sketch of Northwest Quadrant of Baltimore
Served by One Transfer Station 117
6-2 Costs versus Haul Distance for Northwest
Baltimore with and without a Transfer Station 126
6-3 Sketch of Northwest Quadrant of Baltimore
Served by Two Transfer Stations 131
6-4 Sketch of Northwest Quadrant of Baltimore
Served by Three Transfer Stations 132
7-1 Theoretical versus Actual Waste Generation 150
A-l
A-2 Distributions of Housing Units per Net Acre
A-3 by Neighborhood Type in Baltimore 156
A-4
XI11
-------
TABLE OF ILLUSTRATIONS (cont.)
Number Title Page
A-5 Monthly Variation in Solid Waste Production
in Baltimore 159
A-6 Daily Variation in Solid Waste Production in
Baltimore 160
A-7 Distribution of Net Dumping Weights for Small
Collection Trucks 161
A-8 Distribution of Net Dumping Weights for Large
Collection Trucks 161
A-9 Distribution of Traffic Speeds of Collection Trucks 164
A-10 Distribution of Traffic Speeds of Empty Collection
Trucks 164
A-11 Distribution of Traffic Speeds of Loaded
Collection Trucks 164
A-12 Least Squares Exponential Regression of Traffic
Speed on Trip Distance 167
A-13 Least Squares Linear Regression of Log Traffic
Speed on Trip Distance 168
Observed Collection Rates in Neighborhood Type 1 174
r\ — I O
A-16 Observed Collection Rates in Neighborhood 175
Types other than 1
A-17 Assumed Collection Rates for Two Days since 175
A-18 Last Collection 176
xiv
-------
TABLE OF ILLUSTRATIONS (cont.)
Number Title Page
A-19 Time Interval between Truck Arrivals at
Baltimore Incinerators
A-20 Service Times at Baltimore Incinerators
xv
-------
LIST OF TABLES
Number Title Page
1-1 Type of Collection Agency Used in 995 Cities
in 1964 3
1-2 Type of Refuse Collected in 1964 by 1,142
Systems in 1964 ~*
1-3 Frequency of Refuse Collections by Municipal
Agencies in 1964 6
3-1 Variable Conditions for Model 1 Runs 28
3-2 Variable Conditions for Model 2 Runs 32
3-3 Example of Print-Out from Runs of Model 1 and 2 49
4-1 Average Number of Housing Units Served per
Day per Truck 51
4-2 Average Number of Gross Acres Served per Day
per Truck 52
4-3 Results from Three Model 1 Runs with Different
Random Number Sequences ~*6
4-4 Sensitivity of Model 2 Responses to Change in Seasons -"a
4-5 Analysis of Variance Matrix for 5-Way Test on
Variables Affecting Cost °7
4-6 Relative Significance of Variables on Collection
Costs 68
4-7 Percentage Division of Working Day in Different
Activity 69
xvi
-------
LIST OF TABLES (cont.)
Number
Title
Page
5-1
6-1
6-2
A-l
A-2
A-3
A-4
A-5
A-6
A-7
B-l
B-2
D-l
through
D-12
E-l
through
E-13
Example of Print-Out from a Model 3 Run
Data of 13 Subareas Composing Northwest
Quadrant of Baltimore
Variable Conditions for Model 3 Runs
Baltimore Solid Waste Weight Generation by
Month
Relative Significance of Truck Size and Loaded
Condition on Traffic Speeds
Relative Significance of Neighborhood Type
and Collection Frequency on Collection Rates
Distribution of Number of Trucks within Speed
Intervals
Collection Rates per Man and per Crew
Incinerator Service Times
Existing Transfer Station Data
Data of Existing Collection Systems other Than
Baltimore
Tabulations for Cost Calculations, Chapter 4
Results from Model 3 Runs
77
118
122
158
165
171
172
178
179
184
186
188
192
204
XVll
-------
-------
CHAPTER I: INTRODUCTION
This work is concerned with mathematical models which simulate the
working and operation of residential solid waste collection systems in
large congested urban areas. The term "solid waste" here means
combined waste, i.e., combustible and non-combustible rubbish and
garbage. In particular, interest centers around evaluation of proposed
policy changes within a system by use of models rather than evaluation
by temporary changes in actual field operations. It is hoped that the
models will provide tools in this particular field of environmental
engineering which will aid urban decision makers and engineers in wise
annual investments of many mil I ions of dol lars in years ahead .
From twenty to forty per cent of annual budgets of departments of public
works is applied to the tasks of refuse collection and refuse disposal .
Of this repetitive expenditure, approximately eighty per cent is consumed
in collection, the cost of which has been steadily increasing with no
apparent improvement in sanitary quality of service rendered.
So, a problem facing many engineers, city managers, and planners is
-1-
-------
-2-
fhe formulation of new policies which define the solid waste collection
system for the particular city or area for which they have responsibility.
Two objectives guide the decisions; the need to create a system which
does the job in a manner acceptable to the community, and the
necessity of providing service which is economically efficient.
These solid waste collection policies of a city start with decisions made
initially by elected representatives of the citizenry. These few majoi
decisions are then expanded by decisions of less importance as details
are developed. The prime decision at top level is (I) Is collection to
be made by city employees; or (2) Is collection to be made by private:
firms which contract with the city government; or (3) Is collection to
be made by private firms which contract with private citizens. In the
United States the arrangements in 995 cities in 1964 is shown in Table l-l
[American Publ ic Works Association, 1966] . Nearly one-half of repot ting
cities have collection made entirely by city employees, and 65 per cent
have complete or partial municipal service. Only 6 per cent of larger
cities have ordinances permitting contractual agreements between private
citizens and refuse collectors to exclusion of other arrangements.
The extent of collection is an important differentiation between systems.
Garbage is defined as the animal and vegetable waste resulting fiom the
preparation, cooking, and serving of foods. Combined refuse is the mixtuie
-------
-3-
1
, —
<1>
15
,Q
o-
c
(/>
'-^
U
LO
0
0
rn
,E o
O
~o o
OJ — i
ZD r-1
x """'
u _,
£ o
< a
i— t
.2 g.
-"- O
U P-,
1)
"o
U
u-
o
Q.
X
1 —
C
0)
U
i_
0)
Q_
2
o
^_ 13
o -2
~Z. 2
x — s Q)
o "° '-
§ D
"""
1 O
0 0
o o
1 O
o o
o
LO
1
CM
CN
1
O
o
1
u~>
|
-4—
-O
*^ r\ ro LO co r— ~ ^i~ 0*^
- _ _ f>
oo — ro oo r— ' ' '—
\ , —
1 I 1 ^- 1 ,_ 1 tr>
111 1 1
CN OO IX
CO^2^CN|CO'~ C>
CNlOOIXCNOCM O
O OO CM CN • — • — O
cNOrooo^t^ o
x rx TJ- •»*• • — • — LO
— oo
O-^-Ou^. — OOQO O
•— LO -^r •— ^
0)
o
.-
-i- Q_
(J
£ o -
o i ti £
£ 8 c T
T> -a ° Q-
C C U -n ^
° ° - c ~D
Q _4_
8.ti 8- 8. 8. ti £
'u o JH 'u 'u 'u o
c | ^ 'E 'c 'E -£
3 0 •- = D _3 0
5 U ct 5 5 5 U
-------
-4-
of garbage and ashes combined with rubbish, which itself is a variety of
combustible and noncombustible solid waste from household units, stores,
and institutions. If a city government decides to enter the collection
business, the next decision is the extent of col lection . What classes of
waste are to be collected with what frequency? Are all wastes to be
mixed together? One policy may require the citizen to wrap garbage for
twice a week collection, but may collect other wastes only weekly. An
additional limitation of service occurs in cities that deny collection
service to certain classes of property. Such limitation is most often
applied to commercial establishments, industrial sites, and multiple
dwellings. The maximum quantity which will be collected at any one
site is specified in many cities. Table 1-2 [American Public Works
Association, 1966] summarizes practice with regard to class of refuse
in the United States.
The elected city officials rather than the city sanitation department may
make the major decision of frequency of collection . Present practice
tends heavily toward either once per week or twice per week. Table 1-3
[American Public Works Association, 1966 ] gives common practice.
The three major points of policy are: (I) Whether the city will or will not
do the collection with its own employees; (2) Assuming this decision is
-------
-5-
CN
,_^
1/1
o
u
Q)
"5
CN
1 —
_T
X
_Q
3
CN
^
0
u
(U
o
U
(U
U
i_
Q_
C
"•—'
t!
o
u
rx CN CN CN
SI
'B
f~ _Q
.— D
1) 5 0)
P 2 ^
2? «> '^
^ £ E
3 I
£) X -D (J
§ 0 § §
O O U Z
•^t
gj
-o
i\
^>
a>
Q
O
O
D
Abandoned a
IT) . — O LT)
IO "*J CM IX
^o y> c^i u~>
LO CN O IO
^f O CO CN
co •— rx ^t
(U
in
O
£
o
-*—
"" "
"o
^
01
T3
O
0)
C
'•"•
0) -^
tn D
D J3
Industrial ref
Contractors'
Ashes
Dead animal;
in
s
n
in
CO
-------
-6-
0
'o
1_
0>
E
U
•D
C C
D £
-*—
0 0
t— fll
-j_ W
C —
C D
*— f*\
£> "
§1/1
O
U £
*- <
o
X
o
c
0)
cr
0)
k_
u_
-
g
u
0)
U
—
_o
"c
(D
•g
t/i
cS
g
4—
U
(U
o
U
^—
o
X
o
0)
o-
0
u!
1_
0)
E
£
vO "
O^ fl)
6T-— 't-O-— IXCOOOOOO ° j^
^OQp-CO — ^-O-OOxJ-O 2
•=— — — CM 00 2 ~
-4—
D
_C
"*~
E
o
k-
W-
X
•»-
-C
O)
^ -^
•^KiO-OOOOLOOIXO ° X
rt-OOOCOOOOOOOO 2 C
-2^Tt -KJ- oo
1_
(U
•4—
c
i
0)
n -Si
-a> ?
.E -z
TJ 3
C "D
0 „,
Q- v c
£ "o o
•- o> "
« ^ u
d) 0)
'~ O
• — in O
§ -? v E ^
Ed) _^ _5^ t i*-
(1) (U - x
o .* -J5 o * * .> 5 y
»*rggu.ooc: .| g
° 1 2 § s s g^ * 8-
U o o 1 | E | - ^^ g- ^
§ 8 8 8 s „ fi i | .2 g
za^^l^iii^o j5
-------
-7-
affirmative, what types of waste are to be collected from whom; (3) With
what frequency. With these questions answered, details of equipment,
labor, and procedure are normally decided by city managers, city
engineers, and other supervisory personnel rather than by elected
officials. At this level are financial questions, e.g., pay scales for
supervisors, drivers, and laborers, amortization interest rates and times,
overtime policy, pension policy, etc.
Engineering aspects include the method of organizing the work. The
organizational decision is usually made from two al ternatives. These
are (I) Each crew is assigned a particular route for each work day of the
week. The crew must work until collection is made from all households
so assigned. If the work is done before eight hours have passed, the
crew is free to leave and yet still receive a full day's pay. If the day's
assignment requires more than eight hours to complete, the crew must
work overtime. The type of overtime pay arrangement for the last
condition varies with cities. This al ternative is termed the "definite
task" method. (2) The crews work a full eight hour day with many
crews' activities being coordinated and directed by a supervisor. The
areas worked by any crew will be different from day to day and week to
week hopefully in a manner which increases the efficiency of the entire
operation. The definite task method has the advantages that the house-
-------
-8-
holders know the days of collection, and supervision is easy because of
the clear definition of a day's work. Disadvantages include inequalities
of lengths of work days between the first collections of the week and
subsequent ones; also labor difficulties may develop if different crews
collect grossly different daily tonnages. There is the tendency to plan
the assigned routes for conditions when work is slowest and most difficult,
and this results in the situation that only under these conditions is a
full day's work realized.
The preceeding discussion illustrates that the solid waste policy of a major
city is broad in the concepts encompassed. Included are types of property
serviced, frequency with which the service is conducted, type of
equipment and personnel for conducting the operation, pay scales,
amortization schedules and all other peripheral decisions which affect
the efficiency of the operation. Measurements of economic efficiencies
are presented normally as comparisons of cost per ton for similar sanitary
qualities of service.
Comparison of costs of solid waste collection systems between two cities
is questionable. The appraisal of the dissimilar conditions is difficult,
and yet without such appraisal, comparison is not valid. The important
differences which must be considered for accurate cost comparison between
-------
-9-
cities include: (1) climate and geographical differences; (2) form in which
the solid waste is presented for collection; (3) frequency of collection;
(4) place from which collection is made (curb, alley, back door); (5) average
length of haul; (6) wage rates; (7) distribution of population densities;
(8) overtime, vacation, and holiday policies; (9) truck depreciation policies.
On the other hand, comparison of costs of solid waste collection between
two different operating policies within a city or within a particular part of
a city is direct and not subject to differences in many of these variables.
For example, a comparison of costs per ton in a particular city between an
existing policy of overtime pay versus a proposed policy of overtime pay is
a meaningful comparison, direct and uncolored by other system variables.
This study has prepared mathematical simulation models which allow the
latter comparison, but not the former. Three models, titled Model 1,
Model 2, and Model 3, were so prepared .
All models put collection trucks in the field, all express costs in dollars
per ton and record total tonnage collected in some time period. All note
average usage of the hours of the work day by the collection trucks,
whether in collection activity, in traffic between neighborhood and dumping
site, at the disposal site, or in off-route activity, such as truck fueling
-------
-10-
and cleaning, coffee breaks, and lunch time.
The system variables which can be changed in some or all of the models
are:
(I) Household density in households per acre
(2) Haul distance from the neighborhood being collected to
the dumping site
(3) Crew size
(4) Size of truck
(5) Season
(6) Collection frequency
(7) Days since past collection
(8) Pay scale for drivers and laborers
(9) Overtime pay policy
(10) Truck amortization and usage charges
(II) Large transport rig amortization and usage charges
(12) Transfer station amortization and usage charges
(13) Distance from transfer station to final disposal site
The three models are discussed individually below:
Model I, in an individual run, sends several groups of an equal number
of trucks of controllable capacity to collect solid waste from neighborhoods
-------
-11-
of constant density. Each of the groups has haul from collection areas
to dumping site over different controllable traffic distances. Collection
frequency, pay scales, season, truck charges, and days since last
collection are all controllable variables. A sub-routine incorporates
the observed or assumed operating characteristics of the city or tract
being investigated. These characteristics include histograms, regression
equations, and general statements derived from field observations of
traffic speeds, collection rates in pounds per hour by different crews
operating under different conditions, trucks' time at incinerators or
dumping sites, housing units per acre for different neighborhood types,
pounds of solid waste generated per person per day, number of people per
housing units, etc.
A policy of Model I is to operate trucks and crews for as close to a full
eight hour day as is possible. The most important result of this model is
the development of a relationship between number of household units
per truck and the controllable variables.
Model 2 has the same controllable variables and the same data, but more
nearly reflects current practice in that it operates under an "assigned
task" policy rather than an "eight-hour day" policy. Model 2, in an
individual run, sends a number of groups of trucks of controllable capacity
to collect solid waste from neighborhoods of constant controllable density
types. Again each of the groups of trucks has a diffeiont haul distance
-------
-12-
from collection area to dumping site. By the proper combination of runs
of Model 2, comparison of semiweekly collection costs with triweekly
collection costs was made .
Model 3 is a more realistic image of the urban world . It investigates a
tract of a large city with different neighborhood densities; it allows
change of the location of a transfer station within the tract; it allows
the final disposal site to be placed at different distances from the center
of the tract and from the location of the transfer station. For different
combinations of tract area, distribution of neighborhood densities, location
of transfer sites and final disposal sites, the model gives the cost per ton collected
in the system being investigated . Thus, Model 3 can be used by any
urban area considering most changes in operating policies, whether pay
schedules, collection frequencies, or location of or even existence
of transfer stations.
Data concerning field operations have been gathered in the City of
Baltimore. These data portray to a large extent an urban collection
system in the year 1967.
-------
-13-
CHAPTER 2: A SURVEY OF PERTINENT LITERATURE
This chapter is divided into two major parts. The first part is a broad
survey of publications of the post-World War II years of solid-waste
collection practices in America. Little technical reporting on the subject
is found prior to 1941 as the matter only became of major interest when
the increasing costs incident to it and the blighted urban scene resulting
from its inefficient operation finally motivated serious consideration of
new technology. The second part of this chapter reviews literature
dealing with digital computer simulation . This section also discusses
only recent publications, however the recentness of these papers is due
to the newness of the digital computer and the subsequently developed
techniques of simulation of sets of man's or nature's activities. An
important discussion in the second part is of the simulation of a solid
waste collection system which was done at Northwestern University
[Quon etal., 1965] ; it is the only publication found which
combines the two subjects under discussion.
PART I - SOLID WASTE COLLECTION PUBLICATIONS
The definitive American publication on the subject is "Refuse Collection
Practice" (American Public Works Association, 19661; this complete
-------
-14-
book was first published in 1941, revised in 1958, and again in 1966.
It covers current practices, planning, cost estimating, evaluations of
innovations in equipment and procedures, and discussion of systems, per-
sonnel management, equipment management, and accounting and financing.
Typical municipal collection ordinances are included. A large amount of
statistical data derived from cities in the United States and Canada of
more than 5000 population is presented. These include: (I) Population
of reporting cities; (2) Collection system, i.e., whether by municipal
employees or by firms contracting with the individual; (3) Extent of
service, residential, commercial, and industrial; (4) Collection points,
alley, curb, etc.; (5) Frequency of col lection; (6) Method of financing;
(7) Special services by collecter such as carrying cans to and from the rear
doors.
The Sanitary Engineering Research Project of the University of California
[1952] published a bulletin which discusses collection operations in detail .
It attempts evaluation of the affecting variables which in this reference
are termed "influencing factors". It discusses general efficacy of equipmcMif
types and presents typical municipal ordinances and an illustrative design
of a refuse collection system. The most noticable limitation in this otheiwise
complete work is that all costs, weights, refuse compositions, labor hours,
etc. are limited to California data. The scope of the bulletin is widei than
-------
-15-
most; the project staff which authored it included specialists from the fields
of Sanitary Engineering, Soil Science, Mycology, Microbiology, Hydraulic
Engineering, Chemistry, Biochemistry, and Industrial Hygiene.
The American Public Works Association 11964] held a conference on
"Solid Waste Research," in December, 1963; the report resulting from
this meeting included many papers; a few of those which influenced
this study are noted here. Rogus discusses quantities generated and charac-
teristics of urban waste. He attempts to standardize terminology of types
of refuse, units of quantity, and characteristic descriptive terms. Also
the factors believed most affecting the quantity generated are listed.
Various tonnages collected with seasonal patterns from a wide range of
sources are given. Bell discusses characteristics of municipal waste as
found from a project then current at Purdue University. The results are
given from analyzing 2,400 refuse samples from the cities of Milwaukee,
Toledo, Indianapolis, and Bloomington, Indiana. Mathematical and
statistical parameters were used in the investigation of the data and in
the presentation of results. Zanten discusses the existing situation in
waste collection, storage, and transportation; and generalizes as to the
areas where research would be helpful . Lynn indicates what contributions
a system analysis approach may make in the future. The terms, system,
mathematical programming, objective function, stochastic, constraints,
etc., are carefully presented, defined, and put into a context of an
-------
-16-
investigation of a solid waste collection system. Examples of the kind
of statistical information needed for such a study are given. Possible
avenues of such research are illustrated by presenting questions to which
answers are needed. Bowerman presents a concise description of an
existing transfer station's physical equipment and cost. Future trends
in transfer are discussed.
The Ohio Department of Health [ 1965] held a short course in 1965 titled
Technical and Planning Aspects of Solid Wastes. The proceedings from
this short course include descriptions of the several methods of collection
in use in American cities, and the fundamental criteria for evaluating
suitability of the methods by Taylor and by Crane. Lynn describes
systems analysis and simulation, optimization, and limitations of the
results from such efforts.
In July, 1967, the Engineering Research Conference [ 1967 ] sponsored a
meeting for the exchange of information, opinions, and ideas between
researchers in solid waste. Abstracts of the conference reports were
published, and many are being or will be published in their entirety .
Hickman reports on composition and per capita generation of residential
solid wastes in areas of Cincinnati, evaluating quantity variation within
combinations of single family dwellings and apartments with or without
-------
-17-
food grinders and incinerators. The cyclic character of generation of
residential solid wastes and an anlysis of the factors responsible for
the effect is reported by Kennedy. Quon concludes that significant
changes occurred in quantities of refuse generated in two residential
areas as a result of changing collection frequency from once a week to
twice a week.
A study of the Los Angeles County solid waste situation is a very complete
planning effort [ Los Angeles County, 1955] . Definitions of terms are
carefully given; factors affecting costs and manpower and machinery
requirements are discussed in detail . Conclusions reached include:
(I) collection crew size and collection vehicle type do not alter collection
manpower requirements significantly; (2) collection vehicles are generally
inefficient for haul distances greater than five or six miles; (3) the
quantity of waste increased with an increase of frequency of col lection;
(4) approximately 15 per cent more manpower is required for collection
in hilly districts than in level areas; (5) changing collection from once to
twice per week requires increasing manpower by 50 per cent. The report
includes much information on composition and quantities of solid waste and
its seasonal cyclic variation in quantities generated; again this information
is limited to the particular locality with which the report deals.
Many valuable thoughts and discussions of attempts to impiovc- collodion
-------
-18-
efficiency have been published in trade magazines rather than in
professional journals. These are generally authored by men engaged
in the actual task of supervising the collection operation for a city or
a region rather than by those whose interests are peripheral in the area.
Several are noted here because they have particular applicability to this
study. Cole [I960] discusses with enthusiasm the adoption of a transfer
station by the city of Lakeland, Florida and the change in collection
from a daytime operation too nighttime one. Karolevitz [1963] plans
ahead for the area adjacent.to Seattle, Washington incorporating a
series of transfer stations and takes into consideration the unique local
situation that private citizens deliver about twenty per cent of the total
refuse volume. Also complicating the scene are twenty-one licensed
commercial haulers operating in the area. He gives costs and savings
and plans for the future. Koch U9601 questions the current practice of
acquiring disposal sites on a buy-as-needed basis, but in addition he
discusses collection haul costs, land costs, equipment costs, and transfoi
station costs in his particular area of California . King 11960) lists the
circumstances which caused Santa Monica to build transfer stations.
Among them were increasing costs of the system through the yeais and
the difficulties of their old incinerator system with the Los Angeles Air
Pollution Control District. He gives an excellent description of the
physical layout of the transfer station and the compacting mechanism
adopted.
-------
-19-
The review of literature covered decades of isolated tracts dealing with
European and New World municipal sanitation. One considered of
general interest is "Collection and Disposal of Town Refuse" [Organization
for European Economic Cooperation, 1953] . This paper emphasized the
relation of the work to general public health. It devoted chapters to
European methods of those years. Special processes including transfer
stations are described and evaluated. Disposal methods are discussed in
detail along with the major problem of collection of household solid waste;
the European economic feasibility of recovery of papers, edible foodstuffs,
and metals is discussed .
Older references which picture the thinking of the late forties and early
fifties include a summary of lectures given at a training course in refuse
collecting [University of Michigan, 1947] and a report on Refuse Collection
and Disposal Practices [American Public Works Association, 1950J .
Thinking in earlier decades on waste collection was generally restricted
to nonprofessional personnel, who only rarely put their tho ughts and
recorded their practices in publications. The problem and its attendent
costs are only recently brought to public view.
-------
-20-
PART II - DIGITAL COMPUTER SIMULATION
Digital computer simulation is a technique with the objective of giving
insight into the behavior of a complex system. A local optimum situation
may be found by simulating a system under different conditions and then
comparing costs, profits, or operating efficiencies between the results
of the simulations. The references cited here are structured and run for
a look at an operating system or for the determination of a local optimum
value for controllable variables. In all simulations, explicit or implicit
constraints are present, whether the objectives are answers to particular
questions or merely a succession of snapshots of an operating system.
The peak hour traffic in a bus terminal for the Port of New York Authority
has been simulated [Jennings and Dickens, 1958] . The goal is to
evaluate the effect of variances in the length of a single lane bus platform
The model generates the number of passengers arriving every minute, the
arrival time of buses, and operates on the basis of controllable rules
governing the loading of the buses, and entry and exit of buses from
assigned berth positions. The model is programmed to give a snapshot
of the system at the end of every minute. The results are piesentcd in
a manner such that ready evaluation of the influences of platform length
on passenger waiting time and bus holding space is possible. This
-------
-21-
particular paper il lustrates a realistic problem of design which did not
lend itsel f to mathematical or direct analytical investigation, but was
of such structure that simulation study examined and tested it and gave
answers in a form suitable for design utilization, without disruption of
service. This paper is particularly valuable for the newcomer to
simulation as an introductory reading.
Simulation has been used extensively in war games. More publications
seem to be in this area and that of information systems and decision making
in the business firm than in all others. The movement of war games from
the plotting board, with toy ships, aircraft, troops, maps, and incomplete
information for the opposing sides, to simulation on a digital computer was
an easy logical step. Computer generated random numbers have replaced
throws of dice, and programmed march tables, firing tables, and similar
"canned " aids define combat possibil ities. A coverage of war games which
has had stochastic overtones through the centuries is given in [ Griffin, 1965]
He merges basic military gaming with more sophisticated politico - military
gaming and in the end, attempts to evaluate the gains and debits for the
participants. Other books exist on the subject [ Morschaurer, 1962;
Schelling, I960; Zimmerman, 1961.] This last discusses the
evolution of a concept of a war gaming model which provides for the
codification of many of the decision processes occurring in battle, and
-------
-22-
once defined, those decisions may be repeated as often as required .
There results a mathematical model with all the stochastic variables which
directly simulates the step-by-step progress of an isolated battle , This
paper specifically attempts to evaluate the effectiveness of a new tank
design on the combat effectiveness of company sized units.
Information of broadening interest was found in publications from business
administration studies and economic studies. Many were research endeavors
taking into account the large number of interactions and interdependencies
of communications and decision-making within the firm. Of particular
interest are Sprowls and A si mow [1960 1 , Bon in i 119631 , and Forrester [1961] .
Bonini investigates by simulation the effects on the hypothetical firm of
three types of changes. These are: (1) changes in the external environment,
external in the sense of not being controllable by the firm; (2) changes in
the information system of the firm; including the kind of information trans-
mitted, the amount transmitted, and the timing of information flows; and
(3) changes in the decision rules. Forrester [1961] describes simulation
models which include warehouses, factories, wholesalers, retailers, and
consumers. He then "looks at the system" which he has created as precon-
ceived changes in consumer demand, advertising policies, etc., are executed,
Some publications [Maass et al ., 1962; Hufschmidt and Fiering, 1966 |
-------
-23-
discuss problems and goals more familiar to civil engineers than the other
references which are concerned with business and military affairs. Maass
discusses simulation abstractly initially and then the actual simulation
model of a river basin system's behavior for flood control, irrigation,
and power generation . Limitations of simulation particularly with respect
to streamflow and river basin problems are examined. Hufschmidt and
Fiering analyze the application of simulation to a planning problem of
the Lehigh River basin and its extension to simulation of a larger system,
the entire Delaware River basin. The generation of synthetic hydrology
is incl uded.
Conway [1963 ] considers the problem of precision of results obtained
from simulation runs and methods of improving them. Effects of starting
conditions, effects of sample sizes and replications and the nature of
equilibrium in an operating system are examined. Tocher [1965] gives
a concise evaluation and indexing of current simulation languages,
tabulating for the languages such pertinent aspects as the basic language
from which the simulation language is derived, the computer for which
the language is suited, the sampling procedures available in each, the
naming of variables in each, etc. Tocher [1963] deals general ly with
the study of industrial operations and processes by simulation. Sampling
from distributions, sampling methods, random number generation techniques,
-------
-24-
and queuing problems are covered.
The original work which applies digital computer simulation to municipal
solid waste collection is by Quon [1965] . This has as a major objective
the delineation of interrelations between the affecting variables on Hie
functioning of the system. The data upon which the system operation were
based were from the solid waste operations of the village of Winnetka,
Illinois. Haul efficiency and over-all efficiencies are measured in units
of man-minutes per ton rather than in units of dollars per ton. Sensitivity
measurements are made for varying coefficients of variation of the quantity
of solid waste generated per service per week.
-------
-25-
CHAPTER 3: THE POLICIES AND STRUCTURES OF MODELS I AND 2
The purpose of Model I is the determination of the collection potential
and associated costs of a collection truck operating under a set of stochastic
conditions within the framework of an eight hour work day. Because of
stochastic influences, a single run of a truck is not indicative of the
performance which can be expected. Therefore Model I fields thirty
trucks at a time, operating under the same stochastic influences and under
the environmental conditions desired by the investigator. The results of
major interest from this model are the mean, the maximum, the minimum,
and the standard deviation of the number of household units from which
collection was made by these thirty trucks in one day under the particular
conditions of season, neighborhood type, haul distance, etc.
The purpose of Model 2 is the determination of results of assigning a
definite number of household units for collection to a truck for its task
for a day. Again because of stochastic conditions, a single run of a truck
is not conclusive, and so thirty trucks are fielded under constant environ-
mental conditions. The Model I runs necessarily preceded those of Model 2
as the decisions for the number of household units to be assigned in the
latter model were based on the number serviced in the former. The results
-------
-26-
of greatest interest from Model 2 are the unit costs of collection in
dollars per ton for different conditions, particularly different collection
frequencies and different sizes of daily task assignments for the 20 cubic
yard collection trucks.
The information obtained from Models 1 and 2 influenced the aims and
structuring of Model 3.
POLICIES OF MODEL 1
The model simulated the fielding of 180 collection trucks for the purpose
of collection of solid waste . Each run has a constant neighborhood
density for all 180 trucks; other variables held constant for individual
runs are number of days since last collection, collection frequency per
week, season, truck capacity, and size of crew. On each run, Model 1
was programmed so that of the 180 trucks "working", groups of thirty
each were sent to six different collection areas, each area being a
different distance from the final disposal site. These six different haul
distances were: one, four, eight, twelve, eighteen, and twenty-four
miles. Table 3-3 shows the printout of results for one of the groups of
30 trucks.
-------
-27-
The number of haul distances and the number of trucks dispatched to each
can be changed to any values respectively between one and ten, and
between 180 and eighteen; the constraint being that the product of the
number of trucks times the number of distances cannot exceed 180 . Thus,
if an investigator wishes, he may send ninety trucks to each of two neighbor-
hoods to work under the policies of Model 1, with all factors constant for
both sets excepting the two different haul distances. The results of the run
would be a comparison of costs between two alternative disposal sites at
the different distances.
In this study, a total of 24 runs was made with Model 1 . In these different
runs, seasons, number of days since last collection, collection frequency,
and other controllable variables were varied as shown in Table 3-1 .
All time spent by a crew during the day was assigned to one of four
categories: (1) Traffic time between the disposal site and beginning of
collection, and between ending of collection and arrival at disposal site,
excepting flat tires and breakdowns; (2) Collection time, calculated by:
Tc = Wt Col/Col Rate
in which Wt Col = Truck's net loaded rate
randomly generated from a histogram of Baltimore data
for the particular capacity truck,
-------
-28-
TABLE 3-1
MODEL 1 RUNS
Run no.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
25
26
27
28
29
30
31
32
Type
truck*
1
1
1
1
2
2
2
2
1
1
1
1
2
2
2
2
1
1
1
1
2
2
2
2
Days since
last
collection
4
4
4
4
4
4
4
4
3
3
3
3
3
3
3
3
3
4
3
4
3
4
3
4
Neighborhood
type
1
2
3
4
2
2
3
4
1
2
3
4
1
2
3
4
1
1
4
4
1
1
4
4
Season '
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
Collection
frequency
per week
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
Size of
crew
4
4
4
4
4
4
4
4
3
3
3
3
3
3
3
3
3
4
3
4
3
4
3
4
^Truck type 1 is a 13 cubic yard truck 'Season type 1 is summer
Truck type 2 is a 20 cubic yard truck Season type 2 is winter
-------
-29-
and Col Rate Collection rate in pounds per hour
randomly generated from a histogram of Baltimore data
for the particular crew size under the run's conditions
of days since last collection, etc.
(3) Incinerator time, in minutes, randomly generated from a histogram of
truck times at the two Baltimore incinerators; (4) Off-route time, which
included the following: (a) Some time between 50 minutes and 68 minutes,
reflecting two twenty-five minute breaks during the day plus the assumption
that the 180 trucks left the main garage at O.I minute intervals in the
morning, (b) Breakdown time; breakdowns were generated at random;
when they occurred, the truck was charged with twenty-five minutes of
off-route time, (c) In the prototype activities at garages, it was noted
that servicing of the trucks was normally done at the end of the day for
the following day. Also if the crew finished particularly early, the
truck was cleaned by hosing and some minor repairs were made. The
model has the following policies; If truck and crew have already worked
eight hours after dumping, no off-route time is logged by the truck, i.e.,
no servicing or cleaning. If clocktime after dumping is within one hour
of a full eight-hour day, one-half of the remaining work time is logged
to off-route time and the crew is freed the other one-half.
After each dumping of a load by an individual truck, a check is
made of the probability that the truck can, without going on ovc>itirn>i,
-------
-30-
return to its collection area with an expected thirty minutes available for
collection work, and then return in traffic and dump. This determines
whether another load is collected .
A proper combination of random events puts individual trucks on overtime.
A truck can have a flat tire or minor breakdown while on overtime and so
log this off-route time; however, no additional off-route time for coffee
breaks or truck servicing at end of day is used by an overtime truck.
Model 1 is based on the plan that the trucks wor k a full eight-hour day
collecting from as many household units as possible . As the day passes,
the decisions of greatest importance are: (1) after dumping, should
another collection trip be made; and (2) on arrival at the collection
area, does time remain to collect a full load or only a partial load.
All decisions are programmed for the intended completion of the day1 s
work without overtime .
Regular and overtime pay scales, truck maintenance and operation costs,
and amortization rates can each be changed by a single card in the Block
Data subroutine to fit the financial picture of any city. However, the
model is programmed to the policy that overtime pay is paid to the
-------
-31-
next integer hour, as this is current practice in Baltimore.
Figures 3-3, 3-4, 3-5, and 3-7 show flow-charts for the principal
subroutines of Model I .
POLICIES OF MODEL 2
This model is in essence Model I with a single major policy change.
Model 2 has given to each of its 180 trucks a definite task assignment
of some number of household units from which to collect. This task is
to be done regardless of the shortness of workday or overtime necessary
for its completion. No decision-making is programmed in Model 2 to
determine if another trip shall be made or if time permits another full
load or a partial load . The only question asked for each truck is ifall
assigned units have been serviced. The classifications of elapsed time
for the individual trucks are the same as In Model I .
In this study a total of 34 runs were made with Model 2. In these different
runs, the controllable variables were given values as shown in Table 3-2.
The Collection subroutine and the Cinera subroutine are different for the
two models; Model 2 flow charts for these subroutines are shown in
Figures 3-6 and 3-8.
-------
-32-
TABLE 3-2
MODEL 2 RUNS
Run
17
18
19
20
21
22
23
24
33
34
35
36
37
38
39
40
22-2
22-3
51
52
53
55
56
57
71
72
73
75
76
77
81
82
83
84
Days since
last
collection
3
3
3
3
2
2
2
2
4
4
4
4
3
3
3
3
2
2
4
4
4
4
4
4
3
3
3
3
3
3
4
3
4
3
Neighborhood
type
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
2
2
2
2
2
3
3
3
2
2
2
3
3
3
1
1
1
1
Collection
frequency
3
3
3
3
3
3
3
3
2
2
2
2
2
2
2
2
3
3
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
Size of
crew
3
3
3
3
3
3
3
3
4
4
4
4
3
3
3
3
3
3
4
4
4
4
4
4
3
3
3
3
3
3
4
3
4
3
All runs are with 20 yard trucks in summer season .
-------
-33-
STRUCTURE OF MODELS I AND 2
The programs of these models depend heavily on a list processing program
prepared by Dr. Mandell Bellmore of the Johns Hopkins University.
This program served as a core with prototype activities tied about it.
Figure 3-1 shows the general schematic of Models I and 2 while Figure 3-2
shows a more detailed interaction of the Main program with the
33 subroutines. A discussion follows concerning individual subroutines
positioned in the blocks of Figure 3-1 .
MAIN PROGRAM
Two dictionaries are listed at the beginning of the main program, one
of list processing variables and one of simulation model variables. This
program acts as the focal point out of which the Initialization group of
subroutines, the List Processing group of subroutines, and the Result
group of subroutines are cal led .
INITIALIZATION SUBROUTINES
(I) BLOCK DATA; Here in one package are the observed or assumed
attributes of the city or tract being investigated; included arc the costs
-------
-34-
2»
li
< —
\ INITIALIZ
SUBROU1
£
\
CO
Ul
^_ ^
i- p
1 ' — >
— 1 ~J
K °
3 CO
^>
CO
5* H
ccic ujo uj *£ >-
oOH_oQQ-Ct:tt-<
2Oco<:2H;?r5:- z . v.
^"-p u<^
0>g UJ1^^^
o h or E o
o
— CO
co uj
co 2:
Ul —
.1ST PROC
SUBROUT
o
2
or o
u. ^>
CO
Ul
Q
o li
i—
0
X
O CO
^ — 0.
O Z <
o < z
_J Q. CO
UJ y; *~ id
UJ t- 2 x^ CO o
^'i cc x * ^
d3WIJL
\
\
OJ
CO
Ul T3
z c
— J 1— 1
0 w
OC l_ > r-1
co o . or a)
3 g^|| 1
CO QO CL CO "«
H 0
^: o
—> -r-l
co .u
Ul nj
or 6
r—t Q)
\ 1— . 1 (-•
© ©
'
5
«3
fE Q:
n O)
H 0)
I-M O
-------
MAIN
-35-
—| INIT
—[ SSWTCH
DATA IN") [TPAGE 1 1 TODAY ]
DATOu
[—| SUMARY
—| SSWTCH ]
—| INIT 2 ]
—| PANIC"
TIMER ] [ DATMAK
*—[ PRINT
—| CINERA
CREATE |—p-j PANIC
—| XINIT ] 1 FILAST
PACK
UNPACK
PANIC
—| TRAFIC [ [ RANDOM^
BINORM
—| REMFST
PACK
COLECT
STAT
UNPACK
RANDOM
HIST
PANIC
FIGURE 3-2
OUT
Interaction of Subroutines
-------
-36-
of labor and equipment, and the many data which describe the neighbor-
hood densities, collection rates, loaded weights of trucks, histograms of
incinerator waiting times, regression equation parameters of relation
between traffic speeds on trip distances, season constants, waste weights
generated per capita, etc . This mass of city or tract attributes coupled
with the values of the run variables of the DATAIN subroutine coupled
with the decision between Model 1 policy or Model 2 policy encompass
the control possible by the investigator. Studies which desire other variables
or policies necessitate changes in programming.
(2) DATAIN: The run variables are given values here . These include:
(a) the run number
(b) the control parameter, K, for starting the random
number generator. When K is set equal to zero, the
values of the numbers generated are unpredictable
and vary with each succeeding run . When K is set
equal to a positive integer, the sequence of the
generated random numbers will be the same for succes-
sive runs.
(c) the type of truck; Models 1 and 2 are programmed for
two sizes of collection trucks.
(d) the number of days since last collection; values can be
three or four .
-------
-37-
(e) the neighborhood type; four values reflecting
population density are used.
(f) the season; summer or winter.
(g) the collection frequency; semiweekly or triweekly.
(h) the crew size; three or four men.
(3) INITZ: Initializes to zero the accumulators, counters, and entity
attributes in the simulation subroutines.
LIST PROCESSING SUBROUTINES
(I) TIMER: acts with the aid of its utility subroutines as clock or time
base for the events which occur within the simulation model . Its actual
operation is to remove the first ranking event from the calendar of events,
note the type of event, and so to direct model activity properly.
(2) CAUSE: places event notices generated by prototype activities on
the calendar.
(3) CREATE: used only once on each run to create the initial calendar.
(4) FILFST, FILLST, FILRNK: file events at first of list, last of list, or
-------
-38-
in a ranked position, as desired. The list is the calendar in the case
of the CAUSE subroutine.
(5) IDCHK: a precautionary subroutine which checks the validity of
list number cal led .
(6) PACK: combines individual numbers which describe attributes of
an event into a single number; its purpose is to save computer effort and
memory space.
(7) REMFST: removes events from the calendar from the first of list.
In Models I and 2, events were filed in a ranked manner so that the
first in the list was that one which was always next to be removed.
(8) UNPACK: separates the single packed number described in PACK
into its components.
(9) LOOK: allows an interruption to the system's operation for the purpose
of viewing the condition of a specified list (calendar).
(10) PANIC: if an unacceptable condition has occurred in the TIMER,
IDCHK, or UNPACK subroutines, PANIC is called to identify the corient
-------
-39-
event and its attributes and to terminate processing.
(II) SNPSHT: prints the event and its attributes for which the LOOK
subroutine is called.
RESULT SUBROUTINES
(I) DATOUT: prints the controllable run variables which were supplied
by DATAIN subroutine.
(2) OUT: prints the results of the run with alphameric explanations.
(3) PRINT: prints alphameric description of the run, the values of the
run variables, and calls STAT and OUT subroutines.
(4) SUMARY: when trucks have finished their day's work, this subroutine
performs calculations to reduce information to more usable form.
PROTOTYPE ACTIVITY SUBROUTINES
(I) CINE: contains decision policies, the counters, and recording commands
used while the truck is at disposal site. Decision is made here to return
-------
-40-
or not for another load in case of Model 1, and whether or not all units
are serviced in case of Model 2. A counter notes in both models when
all trucks are done for the day.
(2) COLECT: contains collection decision policies, accumulators and
counters for weights, times, acres serviced, units serviced, and leferencc
commands to pertinent system attribute histograms for those times when the
trucks are engaged in neighborhood waste collection .
(3) DATMAK: after the 180 trucks of these two models are assigned
random initial departure times within controllable limits, this subroutine
assigns proper haul distances to the trucks, does the necessary calculations
to give initial values other than zero to the attributes of next event time,
off-route time, and type of event, and calls CREATE and CAUSE so that
this information may be placed on the calendar.
(4) TRAFIC: records the individual truck's time in traffic, both to
and from the collection area. Possibility of flat tires and breakdown
is included .
UTILITY SUBROUTI NES
(1) BINORM: allows random values to be generated from a normal distribution
-------
-41-
(2) CLOCK: used once only to obtain the exact time which starts the
random number generator to insure an independent sequence.
(3) HIST: by first genercting a random number and then entering the
accumulative plot of a called histogram, this subroutine takes a value
from the range of values covered by the histogram.
(4) KPAGE: prints page titles and page numbers.
(5) RANDOM: in combination with BINORM, allows random values to
be generated from a normal distribution with a mean and a standard
deviation which are designated by the user.
(6) RANPER: generates a random permutation of the first N integers.
(7) RNNR: generates a random number from a rectangular distribution
with values between zero and unity.
(8) SSWTCH; allows the operator to interrupt during execution from the
computer console.
(9) STAT: makes the calculations to reduce the attributes of 180 trucks
to their individual means and standard deviations. The maximum and
-------
-42-
minimum of each attribute are found by search.
(10) TODAY: obtains the current date for printing by KPAGE for run
identification.
Flow charts of the prototype activities follow, illustrating the policies
and logic of Models I and 2 .
Figure 3-3 illustrates DATMAK for both models.
Figure 3-4 illustrates TRAFIC for both models.
Figure 3-5 illustrates COLECT for Model I .
Figure 3-6 illustrates COLECT for Model 2.
Figure 3-7 illustrates CINERA for Model I .
Figure 3-8 illustrates CINERA for Model 2.
-------
-43-
NO
DATMAK CALLED BY
TIMER
I
KSTMFS = (STMFST * 10) + 0.5
N TRUCK = TRDSNO * TRNOHL
INCRMT = (DELPEP * 10) + olT"|
~"
KTMDP = KSTMFS + NTRUCK * INCRMT
^ •
CALL RANPER (L. NTRUCK) |
[ I NT = 0
KKK = KTMDP-1
I
| DO 30 I = KSTMFS. KKK |
| NT = L( INT) |
I OR (NT) = Zl /IP.]
J = 1
NT. L.E. (NTRDS* J )
YES
J = J + I
J_
TRFDIS(NT) = DIST J
t
[ TIME (NT) = ZI / 10.
I EVENT (NT) = 1
CONTINUE
[PRINT, "THE LAST TRUCK HAS LEFT THE YARD" I
^'"' i —• •'••-' • . .I, , .. ._ . — — ...... j
RETURN
FIGURE 3-3
Subroutine DATMAK, Models 1 and 2
-------
-44-
YES
[jRAFFIc"]
i
304
RMXDST
NO
VELMU = VELMUK
I
VELMU * RKA + RKB * TH ALPS ( NT, NDR )
I CALL RANDOM ( VELMU , VELSIG, TVELOG )1
I '
[ TRFVEL ^ IP X* TVELOCT|
v rr r> ^~- • - —•* ^ M/-\
p^^c^lS TRFVEL
» rm
* VELM AX ? "> I>I>J
^ \
t
| TRFVEL = VELMIN |
| TRFVEL =VELMAX |
\ ,3O7f
[ TRFTMZ = (TH ALPS ( N TND'R ) / TRF VEL X 60 , |
[TRFHR^TRFHR + TRFTMZ |
i
| RND = RNNR (O) |
| FLATNO =PRBFLT * THALDS(NT,NDRT
I ^
31O
=ORHR +
[ TIME (NT) » TIME (NT) -I- TRFTMT]
TIME(NT) = TIME(NT) + TRFTMZ f FLTLTM~]
YES
318
3i4j r
EVENT(NT) > l.
NO
EVENT (NT)
| EVE NT (NT) = 2J
320 \
\ STRFML^STRFML -hTHALDS (NT.NDRT]
RETURN
FIGURE 3-4
Subroutine TRAFIC, Models 1 and 2
-------
[_COLLECT CALtFO 8V TIMER
-45-
202
C- -~ .
i 10 (?oz. ?oi, ?o*j, ?oqj_,_fJET_vpJ
r-T:.h._-
FcAit nTsi <»iViNo"| f C.AI i HIST r,ivtNG~] [ CAI L HIM MVINT, 1 f r.Ai i ntsr Givtfio 1
MO OF UNIIS PFR NO OF UNITS (•( II NO ')' UNITS PFH NO 'll UNIT1) PI R
I ACRt FOR NF. IIP- I | L*51L L0" Nf !YP' ' J I »f.Ht_TOH Nl KP-_J ] [ Af.HT IORNMVP-4J
cn"^-r_ i -^ r-'r - - - - - '
I RNU - MNNR(O) J
TOO TO (211, ?54), KINTRK I
~- T J
I GO TO (270, 272, 274), (DSLC-I ) I
~'
CALL HIST GIVING
COLLECTION RATE FOR
OSLC -2 AND PROPER NETYP
CALL HIST GIVING I
COLLECTION RATE FOR
LC • 3 AND PROPER NETYPJ
COLLFCT
OSLC
CALL HIST GIVING
COLLECTION RATE FOR
OSLC-4 AND PROPER NET
,R
LTYP|
["COLTMZ • W4T E2 M 60 /COLRAfJ
[jCAL^RANOOM (PNDMII fPNOSIG , PNDPER l]
| PNOZUN-PNOPER H SEASNK (Sf ASONI KDSLS * PERUNINETVP)
--
EJA<> WAIF.? /(PNDZUN « UNACRE i^
ij K^ACRTz N E T AC * CORACRTNFTYPT
QcpTMLZ • silMACR » COL ML K INETyP) / »?80~]
[ UNI TSZ • WAT r Z / PNDZUN ]
fACRE(NT) • ACRE (NT I tSH
[ XX • TIME I NT It COLTMZ * l(TRf PIS ( N?l / 2O ) X 60 T]
^LS_!J9
zzi: 1
[COLTMX • 480 - TIME INTI - (I TJfFOI') IN f I /2O I * 60 T)
"~1
[ TIME (NT I- TIME INT) t COLTMZ |
. TZ
| COLMIL(NT1-COLMTUNT) + COLMLZ
[~COLTM(NTI • COLTMT
f TIME I NT I • TIME INTI »!.
[PRINT! • UR(NT)TT
[UNIT (NT] • UNIT(NT) +UNITSZ
wATFX • WATEZ X COLTMX/COLT MZ~]
COLTMINT) . COLT MINT) « COLTMx"|
[~WATE(NTI • WATEINT I t WAT EX |
[ TRIPINTI • TRIP (NT) t ICOLTMX /COLTMZ f|
ICOLMIL (ND • COLMIL (NT I -f
ICOLM1Z H COLTMX /COLTMZ)
I EVENTINT1- 5 1
- _-J
[HFTURN]
\ ACRE (NTI • ACRE (NT I » 1
IJSUMACH K COITMX /COLTMZlJ
I UNITINfT-IINIT (NlVt 1
|^(UNIISZ H COL I MX / COI TMZ ) I
f TPMF IN7J -1J»I INI) (COI TMxJ
FIGURE 3-5
Subroutine COLECT, Model 1
-------
-46-
IF(TRFDIS(N1 J f 0 1 ) NO • t
If ITRFDtS(NT). EO 4 ) NO • 2
IFITRFOISINT) EQ 8 )NO-3
IF( TRFDIS (N1) EO 12 JND'4
If (TRFDISINTI. EO 16 )ND-5
IF lTRFDIS (NT) EO ?4 ) NO- 6
f~iT(COi FRF EQ 2 ) NO • I "I
Ijf (COLfRF FQ 3)NC_»2_J
__ _.. _ ._
[~UNI1(NT ) • AMNC, NN, NtlfJ
[_UN IliNT f -"UNIT ( £17 H 7 t 0 5IOK M COFFUNfNET
. , , .
.7-] __ - j -r_
I f CAt i Him rnviNG T [ fJiii" HIS? GIVING"! I
I NO or UNIT-? PC R NO OF UNI rs PER I I
I I ACnt FOR NE TYP • ? Af.Rf FOR Nf,TyP-3 I I
L ' — - i ----- -1 l — - — i j
~rn._rvL ____ :_rj • r r . .. r ... jr.zi~~
I CAl L HIST MVPNG 1 ] fAI I HI1T OIVINO |
NO or UNI i", PI n NO or i;Ntn PFH I
[ACRE ron NFTVP-I J JAMJT FOR NFtrp-4]
[ ACRt (Nf ) • UNI! INT ) K r,OOA< M ( Nf T YP)/UNACRE_]
RANDOhM PNOMU , PND'ill
WATE (NTl~"pf RUN"TNf ! Vp") M PN I) Pt R I
» SF ASNK 1ST ASON ) M UNIMNT
ACRF; ( NT) »t COLMLK INFT Y
TRNO • RNNR (oil
CALL HIST GIVING
COLLECTION RATE
FOR OSLC • 2 AND
[ PROPER NETYP
'
CAl I HIST GIVING 1 P CAtl HIST OIVINO
COil FCTION RATE 1 COLLECTION RATE
FOR nsi c • i AND I j FOR ostc • 4 AND
PROPER NETYP j PROPER NtfYP
GO TO IZI4". ?54'».JKINTRKn
izz_-."" :_~:n_
' **.TAZ ' i L**Ti£_B **?J
TT f • ™
WATf Z ' *AT( (NTl - TOTwF(NlT]
n^uiQ
_ . ._ _ rr ~~"
VI NT (Hit • Tj
(/.Of TMJ ^J WA!F 7 K _»>0 ) / COl RAlJ
!T7M"(NTT^cot IM(NI) t7oL7tiii7"J
^TIMr^NTJ-TlMf (NT) * COl.TMzJ
[_Tor*VtS17 ~«"TOT WTTN fT+~WA7F/" ]
FIGURE 3-6
Subroutine COLECT, Model 2
-------
-47-
60 TO (471 , 473), KINTRK
DUMPTM(NT)- DUMPTM(NT) +DMPTMZ
CLKTM -TIME(NT) +OMPTME]
I
CLKTM.GE.48O.
I OVRTMZ • (CLKTM -480.)/607|
[JOVRTM -OVRTMZ J
I
I OOVBTM•JOVRTM |
I—tCOVRTMZ ' OT.OOVRTM ?^>—1
I
I TIME (NT 1 1 . CLKTM |
I
[OVRTMK'OVRTMK-t-l. ]
~~^
IEVENT (NT) -s]
|RETURN|
pTRFTMZ • TRFDIS * 6Q./2o7|
1
[ X2-CLKTM •M2.*TRFTMZ) + 30
—i
l<
I ORTM-(480.-CLKTM )/2.1
CLKTM.GT.420
ORTM • 29
,1 _ L
I OR(NT)«OR(NT) +ORTM |
[ TIME (NT) • CLKTM + ORTM |
|TIME(NT)-CLKTM|
I .
IEVENT(NT)•i|
|EVENT(NT) » 3
RETURN|
FIGURE 3-7
Subroutine CINERA, Model 1
-------
-48-
CINERA CALLED
BY TIMER
471
I RND = RNNR (0) I
I _!__ .
GO TO (471. 473), KINTRKj>-
473
CALL HIST FOR
TRUCK TYPE 1
DUMP TIME
I
CALl HIST FOR
TRUCK TYPE 2
DUMP TIME
. L_
[DUMPTM (NT) = DUMPTM (NT) + DMPTMZ |
~T ,
[ TIME (NT) - TIME (NT) + DMPTMZ ]
YES
ORTM M48O- TIME (NT) / 2
OR(NT) = OR (NT) +OFJTM
[EVENT(NT) » i |
fRETURN
[ EVENT(NT) - 5]
|_RETURN~|
("OVRTMZ = (TIME (NT) - 48O.)/60. I
-- - -
= OVRTMZ
IOOVRTM = JOVRTM
YES
OVRTMZ.GT.OOVRTM
NO
OVRTM(NT) ° JOVRTM + 1
fpV R
ovRTM(NT) = JOVRTM]
zzz
EVENT (NT) '5
RETURN"]
FIGURE 3-8
Subroutine CINERA, Model 2
-------
-49-
TABLE 3-3
A PART OF THE PRINT-OUT OF RESULTS
FROM A RUN OF MODEL 2
Tonnage Collected
Gross acres covered
Housing unit collected
Number of trips
Quitting time, hours of work
Traffic miles
Collection miles
Percent time collecting
Percent time in traffic
Percent time in dumping
Percent time off route
Collection cost per gross acre
Total cost per gross acre
Haul cost per ton
Collection cost per ton
Total cost per ton
Number of trucks on overtime
Average
9.13
189.46
812.00
2.03
7.83
48.80
19.74
54.81
20.87
2.55
21.77
0.39
0.69
2.61
7.22
12.79
9.00
Sigma
0.39
76.68
0.
0.18
1.30
4.38
7.99
13.19
4.74
1 .08
10.25
0.20
0.24
0.47
2.95
2.35
Maximum
9.88
416.29
812.00
3.00
11.45
72.00
43.36
76.99
40.27
5.58
45.23
0.96
1 .24
4.34
14.62
19.11
Minimum
8.45
105.69
812.00
2.00
6.09
48.00
11.01
28.73
12.50
1.22
7.48
0.12
0.25
1 .88
3.11
10.77
Each run of Models 1 and 2 produced six tables similar to the above. Each
of the tables gave results for 30 trucks operating at the same haul distance,
I, 4, 8, 12, 18, or 24 miles. A lead statement before the tables gave
other run conditions of neighborhood type, season, collection frequency, etc
-------
-50-
CHAPTER 4: RESULTS FROM MODELS 1 AND 2
A . Number of housing units serviced by g truck per day
Model 1 was programmed to simulate individual trucks working a full
eight hour day yet hopefully not on overtime. As in actual operations,
some trucks in the model found traffic slow, dumping time long, and
themselves on overtime. Runs of Model 1 combined semiweekly and tri-
weekly collection frequencies with the four neighborhood types for two
sizes of collection trucks. The term "run" is used here for the simulation
of the activity of six groups, each of thirty trucks, all collecting solid
waste under the same variable values of days since last collection, neigh-
borhood type, season, collection frequency, and size of truck. However
each group of thirty trucks has a different haul distance from its collection
neighborhood to the disposal site.
Tables 4-1 and 4-2 show the average number of households served and
the average gross acreage from which collection was made by the larger
trucks. Figure 4-1 may be used for preliminary planning as it gives the
average number of households which may be serviced as a function of the
variables which most strongly affect the result. In general, the smaller
trucks served from 85% to 95% of the number of units shown for the larger
-------
-51-
CN
CO
LO
LU
_l
LO
U
z
j~> co
o
•=)
•j:
o_
h-
Z
6
z
z
" oo
5
_i
X
o~
t—
Z
O
z
z
Z)
10 oo co o
r\ oo co oo
• — CN OO CN
CO -O -
< f*
-------
-52-
CN
oo
•
oo
LU
z ~
LU
U
z
00 00
Q
i
Z>
X
"*
r—
o_
(—
LU
Z
6
z
z
Z)
C£
IV -^- O 00
OO -O •**• CN
00 CN CN O
OO hv -r)- CN
*~
O K 00 O
O O uo CN
OO O 00 •—
r*^ o* in c?
00 OO .— |\
CN O -O OO
CN •—
CN O- l\ CN
LO ro i\ ^i"
CN i—
•— CN OO Tj-
IO 0 IV OO
(J
z
LLJ
Z)
0
LU
u_
z
0
h-
(J
LU
— 1
1
o
u
>-
1
LU
1 [ 1
^>
1
^r
CN
oo
1 —
CO
LU
— 1
^CN
LU
u
z
1—
00 oo
Q
13
X
^
^~
Q_
H-
LU
z
6
z
z
Z)
or
IO CN CN O
r*** ix> u~> c^)
r\ CN o -t
r— O LO 00
CN —
O LO OO —
00 CN fx. "*t
CN —
o- oo r-v, r\
.— •— -o oo
CN •—
•£) O- O -O
oo ix O -TJ-
CN •— •—
•^ N. OO ^O
r\ "^f oo ^
CN •—
— CN 00 -
II i Q^
H) ii i
0 ^K
LU J-J] U
LL. ^" Q^
z < *~
O 1 00 LU
r— s-\
{-) —i £x ^
=1 u?° Q
o *~g 2
V_x ^^ ^ O
. "-1-1
— J CO
LU ^
LLJ Z)
^> /— -
1—
-------
-53-
9
S1INH dO •ON
S1INO dO 'ON
TJ
01
I
-------
-54-
trucks for the same run conditions. Figure 4-2 is of less general applica-
tion, as the results in it are completely dependent on the ratio of gross
acres to net acres in the city of Baltimore .
B . Sensitivity of responses to different random number sequences
Twenty-four values of results from each of three successive runs are shown
in Table 4-3. All affecting variables were held constant, but the
stochastic events were generated by different random number sequences.
Figure 4-3 shows graphically some of the same values.
C . Sensitivity of response to season
Model 1 gave the average number of units which could be serviced by a
single truck under controlled conditions of haul distance to incinerator,
neighborhood type in which collection was being done, type of truck, etc
Model 1 also gave the average unit cost of the entire day's operation for
the thirty trucks involved in dollars per ton. The data showed no statis-
tically significant difference in the collection rates between summer and
winter, but did indicate significant difference in the pounds per person of
solid waste generated. Table 4-4 shows results from six runs of these
models made for the purpose of observing season effect on unit costs and
on the average number of units which an individual truck could service
in a day. Figure 4-4 shows the same information graphically.
-------
-55-
S3HOV SSO«9
S3MOV SSOM9
S3HOV SSOH9
S3HOV SSOW9
(U
13
ctf
Q
0)
fc
a
to
-------
-56-
u
CM
CM
C
e*:
CO
i
CM
CN
C
^
1
CN
CN
C.
D
Cxi
C.
"
^
X
2
^
•a >
*- Q)
r> O
§
c
^
^
X
D
D >
C 0
C
o
*~ (D
?> Q
c
s
5
oo
.
rx
CM
rx
00
O
o
CO
IX
rx
rx
co
•
rx
o
IX
00
0
CO
0
o
CN
IX
in
CM
tx
CO
CM
CO
CM
co
o
X,
rx
JU
u
a»
~o
(J
CN
0
CN
O-
O
^j.
CN
r\
CM
0
-o
X
CO
CO
CN
o
CN
rx
v_
0
J
o
o
I
CN
O
CO
CN
IX
O
O
00
in
-o
IX
•
CO
CO
-o
rx
oo
in
o
"^
CN
^1-
co
CO
•o
^o
CO
rx
0
IX
^
CO
c
0)
~o
u
0)
E
P
c
0)
U
L_
CO
.
o
1 —
m
o
CO
-o
CO
X,
CM
CM
,—
.
in
•
CN
O
co
^.
CO
CN
^_
CN
CO
O
1 —
CO
,__
CO
o
CO
- ;
co
CN
O
"E
f—
c
_E
f—
c
a>
(J
£
•o
.
o
1 —
o
CN
^5
-—
ro
X
o
CN
CO
O
CM
o
1
O
rx
2
8
—
CN
CM
.—
• —
CM
in
o
r—
in
o
^.
•—
oo
rx
o
CO
t—
' —
0
t—
l_
8.
2
CO
o
U
1
1
,
—
1
1
1
CM
1
1
1
CN
1/1
D
I —
(U
E
-4—
(U
6
o
o
Z
Q
O
O
U_
OO
Z
Z)
co Z
I LLJ
^ Q
^ Z
—i n i
CO Q_
•<( ULJ
I- Q
Z
co
on
_
0)
I/*
»" X
o ° o
o x--
o -S
CN
(U
o
-Q
_a
CM
T3
C
O
O
00
E
E
J- ° U)
S § o J? a. aJ
— => o 'E -£"•-
S S"^ f TZ-o
.£ ^ o -g, o .2
"> cr >., r-
HI 111
"o — "u "3 -S5 ^
§ -o E § "> ^
4 u £ x Z. u
-------
9.0
8.0
TONNAGE
COLLECTED
PER DAY
PER TRUCK
7.0
6.0
j_
I
MAX
MIN
I
22-A 22-8 22-C
RUN NUMBER
-57-
COST
$/TON
I5.00r
14.00
13.00
12.00
11.00
10.00
MAX
22-A 22-B 22-C
RUN NUMBER
FIGURE 4-3
Sensitivity of Results to Different Random Number Sequences
-------
-58-
Tj-
CN
OO
Q
3
0
X
oo
•
E ^
D iC
co ^
in in
— CN
•O -O
in •*
o -o
x x
^o
0)
o o -o
•-in CN
t rx x>
a)
t/>
i/i
^.
'c
• IX O
0 CN 0
Z OO CN
""'
r> ^
in —
CN ^>
in oo
• — CN
— CO
•^J- rj-
00 CN
CO
u.
0> »-
E £
E .c
D IT
CO ^
Q
UJ
u
o:
LLI
CO
CO
Q
1
o
•n
LU
CO
Z)
O
T:
u_
0
ct;
LU
OQ
5
Z)
z
z
*+ o
4 5
LU Z
U-J J—
_l <
IP
I— co
u
t—
z.
— \
— /
7
6
z
o
CO
LU
CO
U_
O
>-
1—
>
1—
CO
z
LI 1
OO
-------
20.00h
$/TON
10.00
NEIGHBORHOOD TYPE= I
NEIGHBORHOOD TYPE = 4
SUMMER
WINTER
4 8 12 18 24
HAUL DISTANCE, MILES
I50O
NO. OF
UNITS I00°
SERVICED
5OO
NEIGHBORHOOD TYPE =4
SUMMER
WINTER
I I I I
I 4 8 12 18 24
HAUL DISTANCE, MILES
FIGURE 4-4
-59-
Sensitivity of Results to Seasonal Effects
-------
-60-
D. Cost comparison of semiweekly and triweekly collection frequencies
Model 2 gave average unit cost in dollars per ton for thirty trucks operating
a full day under task assignment of u households per truck. The u
assigned was that which Model 1 had produced under its similar program,
which had a workday closely averaging eight hours.
For semiweekly collection frequency, the trucks in Model 2 were assigned
the y obtained from Model 1's run with the same variable values of
neighborhood type, haul distance, truck type, etc., and with four days
having passed since last collection. This number of households continued
to be the assignment for the trucks' second passage over the route during
the last half of the week. Three days since last collection is programmed
for this latter collection of the week. This arrangement results in a longer
average workday and a greater average tonnage for the first trip of the
week than for the last. For this hypothetical route, the tonnage collected
for the week is the sum of the tonnages for the two days; the total cost of
the week is the sum of total costs of the two days; and the unit cost is
this total cost divided by total tonnage .
For a triweekly collection frequency, the tonnages collected from three
days' activities were summed; the total costs of three days' activities were
-------
-61-
summed; and a quotient of dollars per ton was found. The first of the three
days' activities was programmed in Model 2 with a p assignment of house-
holds equal to that average given by Model 1 under the given conditions
with three days having passed since last collection. This p number of
households was also the assignment for each truck both for the second and
third collections of the week. Two days since last collection are programmed
for these last two collections of the week. This arrangement again resulted
in a longer average workday and a greater average tonnage for Monday
and Tuesday than for the remaining four workdays of the week.
To illustrate:
TRIWKCOS = cost in dollars per ton of triweekly collection from a
neighborhood type 1 with a haul distance of 8 miles
DOLCOS17 = average day's cost for a truck with haul distance of
8 miles, from Run 17
TOTTON17 = average total tonnage collected by a truck with haul
distance of 8 miles, from Run 17
DOLCOS21 = average day's cost for a truck with haul distance of
8 miles, from Run 21
TOTTON21 = average total tonnage collected by a truck with haul
distance of 8 miles, from Run 21
-------
-62-
TRIWKCOS = PQICOS 17 + 2 (DOLCOS 21)
TOTTON 17+2 (TOTTON 21)
Tables D-l through D-6 in Appendix D show data from runs and tabulation
of calculations.
Figure 4-5, 4-6, and 4-7 show unit costs of semiweekly and triweekly
collections by neighborhood types. These plotting arrangements allow
comparison of costs either with neighborhood types as the primary variable
being compared or with the collection frequency as the variable of primary
interest.
Most urban collection systems in the United States are of semiweekly fre-
quency. An attempt has been made to approximate the cost increase if
triweekly collection became common . Figure 4-8 summarizes the answers
which Model 2 gave to this question . Two envelopes are drawn; one for
the least densely populated neighborhood type 1 and the other encompassing
the complex of points from the three denser neighborhood types.
E . The relative effects of variables on unit costs
A five way analysis of variance study was made to determine the signifi-
cance of different variables on the cost in dollars per ton of the entire
collection operation. The variables studied were:
-------
20.00r-
$/TON
10.00
NEIGHBORHOOD TYPE = I
NEIGHBORHOOD TYPES 2, 3, 8 4
2 COLLECTIONS/WEEK
I
I
I 4 8 12 18 24
HAUL DISTANCE, MILES
FIGURE 4-5
Collection Costs
20.00
$/TON
10.00
NEIGHBORHOOD TYPE=I
NEIGHBORHOOD TYPES 2, 3, 8 4
3 COLLECTIONS/WEEK
I 4 8 12 18 24
HAUL DISTANCE, MILES
FIGURE 4-6
-63-
Collection Costs
-------
-64-
»,
\t
\ I
\»
\»
\ 1
X A
\« ~
ac\\ *
UJ I1, uj
UJ \\ UJ
* V, *
•T i1 -•.
^ j
3 U8
.L
\
I «
D 0
D O
5 c5
M —
*""
'•
UJ
Q.
^-
H
Q
O
O
NEIGHBORH
i i
* —
CM
CO
UJ
_J
00 —
2E
•*
UJ
o
»,
J-
co
CO O
_J
-
O
I-
l\
1 \
\
1 \
1 *
M t
\ »
id\ » *
UJ \ 1 UJ
UJ I t UJ
at \ \ *
^ \ \Z
° \ :°
0 \ 1 0
10 x 4 CM
l\
> 0
3 O
5 c5
—
H
UJ
Q.
1-
O
O
o
X
ce
o
CD
X
0
UJ
z
CM
CO
UJ
9
JC
•»
UJ
o
CM Z
- <
CO
00 O
^1
z
o
\
I.
1 . 1,1
1\ w
z\\ *
1x1 11 -J
\ u o
o V w
o >V
",\
D O
D 0
5 o
VJ —
CM
II
111 —
UJ
QL
X
o
o
o
x
cc
o
CD _
X
o
UJ
z
_
CM
CO
UJ
cod
~ 2
UJ
0
C^ it^
~
-------
-65-
1.20
to
o
UJ
jjj 1.10
i
UJ
CO
to
o
o
^ I.OO
UJ
UJ
3;
DC.
.90 Li
NEIGHBORHOOD TYPE =1
NEIGHBORHOOD TYPES =2. 3, a 4
"••••,
•c
I 4 8 12 18 24
HAUL DISTANCE, MILES
FIGURE 4-8
Summary of Cost Comparision of Semiweekly and Triweekly Collection
-------
-66-
1) Capacity of trucks, three tons and five tons
2) Density per acre of housing units, less than ten units and
more than forty units
3) Seasonal conditions, summer and winter
4) Days since last collection, three and four
5) Haul distance, four miles and eight miles
Table 4-5 is the matrix for this study. The relative significance of the
variables on the cost is indicated in Table 4-6.
This shows significance is indicated at the 0.001 level for Housing Density.
Significance is indicated at the 0.05 level for the effect of the number of
Days Since Last Collection, the effect of Haul Distance, and the two-way
interaction of Housing Density and Days Since Last Collection .
F . Percentage of worktime in different activities
The Models gave averages of times spent by trucks in different activities
during the day. Table 4-7 gives average values for two runs showing
time divisions for the different combinations of two neighborhood types and
six haul distances. Figure 4-9 shows the same information graphically.
-------
-67-
1 y
~
•s^
a;
LU
O
C£
-1
sx
=5
I—
_i
_i
<£
^
CO
1
X.
>:
jj
z
H
Q_
1 —
jj
Z
if
a.
>-
i—
LU
Z
T
O-
LLJ
Z
u.
C
^*
i_
CD
£
CO
o5
^
^
0)
E
E
CO
ju
C
>
E
E
CO
!_
0)
c
^
0)
E
E
CO
"*
oo
^«
oo
^J.
ro
^
CO
^
n
"*
ro
t
*
v^
X)
^>
»
•3-
30
^f
X)
t
X)
*•
X)
^"
X)
•^r
X)
•*
X)
rt
XI
«.
X)
^-
X)
^
X)
•^t-
X)
*
X)
<*
x>
^
1 1 1 1 IXI 1 IXXXXXX
1 1 1 IXXI IXXXIXI 1
1 1 IXIXIXIXIXIXI
1 1 IXXXIXXXI 1 1 IX
1 IXI IXXI 1 IXXI IX
1 IXIXXXIXIXI IXI
1 IXXIXXXI 1 IXXI 1
IIXXXXXXXIIIXXX
IXIIIIIIIIIIXXX
IXIIXIIIXIIXXII
IXIXIIIXllXIIXI
IXIXXI IXXIXXI IX
IXXIIIXIIXIIIIX
IXXIXIXIXXIXIXI
IXXXIIXXIXXIXII
1 XXXXI XXXXXXXXX
XI 1 1 1 1 1 1 IXXXXXX
XI 1 IXI 1 IXXXIXI 1
XI IXI 1 IXIXIXIXI
XI IXXI IXXXI 1 1 IX
XIXI 1 IXI 1 IXXI IX
XIXIXIXIXIXI IXI
XIXXI IXXI 1 IXXI 1
XI XXXI XXXI 1 IXXX
XXI 1 IXI 1 1 1 1 IXXX
XXI IXXI IXI IXXI 1
XXIXIXIXI IXI IXI
XXI XXXI XXI XXI IX
XXXI IXXI IXI 1 1 IX
XXXI XXXI XXI XI XI
XXXXI XXXI XXI XI 1
xxxxxxxxxxxxxxx
u
•"-J t/}
IX") _•—
^"^ LJ £Q ^J f^ ti J f J ^N . fl {j f LI J
^^
X
90'OL
£8 '8
fil'8
ZC'Z
Ol'OL
06 "8
6G ' 8
8£'Z
*£' 1 I
O/'ll
96'ZL
OS'OL
96 'f [
96' 11
£6" LI
Z9' 1 1
ZO' 1 1
99 '6
ZQ'8
Z/'Z
1 Z'Ol
81 '6
Ofr'8
SZ'Z
IKEL
It-' LL
f
2^'tl
§9'ZL
6?'Cl
frZ'21
1 / * 7 1
zo'n
en
n_i
2 §
•^f -^~~
^^ ^S)
X
•*—
1 -<
•t •£•
UJ (1)
— ' o
< 0
H- •—
O
O
•—
X
"o
c
<
-------
-68-
Source of Deviation
Sum of Degrees of Mean
Squares Freedom Squares
Fraction
A
B
C
D
E
AB
AC
AD
AE
BC
BD
BE
CD
CE
DE
Capacity of Trucks
Housing Density
Seasons
Days since last Collection
Haul distance
Two way interactions of
Trucks and Housing Density
Trucks and Season
Trucks and Days
Trucks and Haul Distance
Housing Density and Season
Housing Density and Days
Housing Density and Haul Dist.
Seasons and Days
Seasons and Haul Distance
Days and Haul Distance
3.10
103.25
0.26
7.24
7.35
0.32
0.33
0.05
0.06
0.83
5.46
0.03
0.37
0.13
0.33
3.10
103.25
0.26
7.24
1 7.35
0.32
0.33
0.05
0.06
0.83
5.46
0.03
1 0.37
1 0.13
1 0.33
3.22
108.66**
0.2»
7.51*
7 . /3*
0.34
0.35
0.05
0.06
0.87
5.74''
0.03
0.39
0.14
0.35
Error
15.12
16
0.951
* F(I,I6)0.05 = 4.54
** F(l,16)0.001 16.6
TABLE 4-6
Relative Significance of Variables on Costs
-------
-69-
•*—
c
8.
i/i
<]>
_E
*~
O
c
0)
U
o3
Q_
"D
0
a:
J.
O
^_
1
_c
"o
c
o
Jj£
*-4—
£
O)
•4—
U
0)
"o
U
•4—
15
"5
D
X
Q.
1—
7.
c.
D
Qi
OOOOOO OOOOOO
oooooo oooooo
NO oo •— • *•"" "^x co to 'T*T r^v *o "^j~ c*o
— — CNOJCNCN —'— — •— CNCN
-O CM CO •— \ ^ OCVJOCMIXIO
CNCNCNICNCO CSCOCOCNCO
•^•fxCOUO^O • — OO3OOO
•— ^* OO CM 3O ^ ^-^ODCMOO-
-j- D
(U M-
U o
o
Z
-------
-70-
co
a)
AVQ ONIXdOM JO %
VJ
(U
••-I
0
cr>
i
-------
-71-
G . Effect of varying the number of assigned units
Model 2 was programmed so that each group of trucks, thirty in number,
was assigned a definite number of household units per truck per day.
This number was the mean of the number of households serviced in Model
1 under similar conditions of the affecting variables, collection frequency,
neighborhood type, etc . It seemed possible that this mean might not be
the optimal number for assignment . Perhaps a smaller assignment might
remove all trucks from overtime and so lower the cost per ton; or perhaps
a larger assignment would cause all crews to work at least the full eight-
hour day for which they received pay and so lower the cost per ton .
The following runs were made to secure results for comparison of dollars
per ton costs of semiweekly collection under the conditions shown:
-------
-72-
Run
Number
34
51
52
38
71
72
35
55
56
39
75
76
33
81
83
37
82
84
Assigned
Task
u
y - 0
y + 0
M
y _ 0
y + a
y
y - a
M + a
y
y - o
y + o
y
y - o
y + a
y
y - o
y + o
Days since last
Collection
4
4
4
3
3
3
4
4
4
3
3
3
4
4
4
3
3
3
Neighborhood
Type
2
2
2
2
2
2
3
3
3
3
3
3
1
1
1
1
1
1
Tables D-7 to D-12 in Appendix D give the results from the above and
calculation tabulations.
-------
-73-
After making these runs, no inflection points were within the range
investigated; therefore four more runs were made for the purpose of
extending the curves in the direction of decreasing cost values.
Run Assigned Days since last Neighborhood
Number Task Collection Type
53
73
57
77
p + 3a
y + 30
M + 3°
y + 3o
4
3
4
3
2
2
3
3
The results from the above and calculation tabulations are also in Tables
D-7to D-12 in Appendix D.
Figure 4-10 shows cost results graphically. The curves decrease asymptotically
in the direction of increasing task assignments. Figure 4-11 shows the number
of trucks out of each set of thirty which went on overtime for the indicated
conditions.
-------
-74-
ro
o
o
o
X
DC
o
CD
X
CD
O
q
o
C\J
o
q
in
o
q
6
o
q
in
1SOO N01/$
CVJ
UJ
Q
o
o
a:
u_
w>
UJ
UJ
a
Q
O
O
I
tr
o
CD
X
LU m
Q <
b
10
""• <
or >
o
u_
UJ
Z UJ
o
I
UJ
in
=>
o
i
O
q
d
(M
O
o
o
o
o
q
in
1SOO N01/
tr
UJ
m
o
tr
UJ
CO
o
o
o
X
O UJ
CD a.
x >
ii (A
tc
a.
tn
* ir
V) Ul
< >
t- <
Q UJ
UJ I
CO —
O
r-l
I
o
O
q
d
CVJ
o
q
in
o
q
6
O
q
in
d
01
(50
cn
en
H
>.
^H
•H
Q
-------
-75-
30r
NUMBER
OF
TRUCKS
ON
OVERTIME
20
10
NEIGHBORHOOD TYPE 1
I 4 8 12 18
HAUL DISTANCE
24
NEIGHBORHOOD TYPE 3
30r°
NUMBER
OF
TRUCKS
ON
OVERTIME
0
I 4
8 12 18
HAUL DISTANCE
FIGURE 4-11
Number of Trucks on Overtime with Different Daily Tasks
-------
-76-
CHAPTER 5: THE POLICIES AND STRUCTURE OF MODEL 3
Model 3 has been described briefly in Chapter I . A more detailed dis-
cussion follows, giving the nature of the model, the controllable variables,
the range of values which may be given them, and the mechanics of
usage.
Frequent reference will be made in this chapter to a "run" of Model 3.
A run simulates collection activity by 20 cubic yard collection trucks in
a particular urban area for one week, Monday through Saturday. The
area may be composed of many subareas of different population densities,
all having solid waste collection being made by one agency under a set
of policies which remain constant for the entire week. A transfer station
may or may not be present in the model . Model responses include the
week's costs in dollars per ton of the collection trucks operation, of the
transfer station operation, and of their sum. Mileage figures, distribution
of overtimes, summation of trips made, tonnage by days, costs by days,
average length of working days, etc ., are also presented . Table 5-1 is
a sample of Model 3 results.
-------
-77-
SOMD WASTE COLLECTION SIMULATION RUN NUMBER 23
MODEL THREE
THIS IS A SIMULATION RUN ON A PORTION OF THE CITY
OF BALTIMORE, APPROXIMATELY DESCRIBED AS 'THAT TRACT
BOUNDED ON THE NORTH BY THE CITY LIMITS, ON THE EAST liY
YORK AVENUE, ON THE SOUTH BY NORTH AVENUE, AND ON THE
WEST BY THE CITY LIMITS.1
WITHIN THIS TRACT, 13 RESIDENTIAL AREAS, EACH OF
PARTICULAR HOUSING DENSITY, HAVE BEEN GIVEN NUMBER DES-
IGNATIONS FROM I TO 13. TABLE ONE BELOW LISTS THESE
AREAS AND DATA PERTINENT TO EACH. 24 COLLECTION TRUCKS,
ALL COMPACTER TYPE ARE OF 20 CUBIC YARD CAPACITY, HAVE
BEEN ASSIGNED TO THESE 13 AREAS TO MAKE COLLECTION 2
TIMES PER WEEK.
THE CREWS ASSIGNED TO THt TRUCKS ARE A DRIVt'R AND
THREE LABORERS ON MONDAYS, TUESDAYS AND WEDNESDAYS, AND
A DRIVER AND TWO LABORERS ON THE REMAINING DAYS.
TABLE TWO LISTS THE ASSIGNED COLLECTION TRUCKS BY
NUMBER AND LISTS DATA PERTINENT FOR EACH.
TABLE 5-1A
-------
-78-
*•* TABLE ONE »**
AREA
NUMBER
1
2
3
4
5
6
7
8
9
10
11
12
13
NFIGHfUW-
HtJOO TYPE
I
2
1
2
3
2
1
2
3
4
4
3
3
HOUSING
UNITS
TOTAL
5711
1099
6124
2079
11186
96b9
7299
1887
5906
10519
6/31
2317
3937
TRUCKS
HAUL
MILES
3.28
^.25
2.35
1.31
0.49
2.39
1.57
2.3?
1.69
3.05
3.30
2.59
3.24
ASSIGNED
UNITS PtR
TRUCK
951
1099
1020
1039
1118
1207
1042
943
1181
956
961
1158
984
NUMBER
OF
IUKJTI
6
1
6
2
10
8
7
2
5
11
7
2
4
S
TABLE 5-IB
-------
-79-
**» TABLE TWO *»»
TRUCK
NUMBER
1
I
1
2
2
2
3
3
3
4
A
4
5
5
5
6
6
6
7
7
7
8
8
8
9
9
9
10
10
10
11
11
11
12
12
12
13
13
13
14
ASSIGNED
TO AREA
1
1
1
1
1
1
2
3
3
3
3
3
3
4
4
5
5
5
5
5
5
5
5
5
5
6
6
6
6
6
6
6
6
7
7
7
f
7
7
7
UNITS TO
COLLECT
951
951
951
951
951
951
1099
1020
1020
1020
1020
1020
1020
1039
1039
1118
1118
1118
1118
1118
1118
1118
1118
1118
1118
1207
1207
1207
1207
1207
1207
1207
1207
1042
1042
1042
1042
1042
1042
1042
HAUL
DISTANCE:
3.28
3.28
3.28
3.28
3.28
3.28
2.25
2.35
2.35
2.35
2.35
2.35
2.35
1.31
1.31
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
2.39
2.39
2.39
2.39
2.39
2.39
2.39
2.39
1.57
1.57
1.57
1.57
l.5t
1.57
1.57
NEIGHBOR-
HOOD TYPE
1
1
1
1
1
1
2
1
1
1
1
1
1
2
2
3
3
3
3
3
3
3
3
3
3
2
2
2
2
2
2
2
2
1
1
1
1
1
1
1
DAYS TO
COLLECT
MONTHU
TUEFRI
WtDSAT
MONTHU
FUEFRI
WEDSAT
MONTHU
TUEFRI
WEDSAT
MONTHU
TUEFRl
WEDSAT
MONTHU
TUEFRI
WEDSAT
MONTHU
TUEFRI
WEDSAT
MONTHU
TUEFRI
WEDSAT
MONTHU
TUEFRI
WTDSAT
MONTHU
TUEFRI
WEDSAT
MONTHU
TUEFRI
WEDSAT
MONTHU
TUEFRI
WEDSAT
MONTHU
TUEFRI
WEDSAT
MONTHU
TUEFRI
WEDSAT
MONTHU
TABLE 5-1C
-------
-80-
*•* TABLE TWO »**
(CONTINUED)
TRUCK
NUMBER
14
14
15
15
15
16
16
16
17
17
17
18
18
18
19
19
19
20
20
20
21
21
21
22
22
22
23
23
23
24
24
24
ASSIGNED
TO AREA
8
8
9
9
9
9
9
10
10
10
10
10
IU
10
10
10
10
10
11
11
11
11
11
11
11
12
12
13
13
13
13
0
UNITS TO
COLLECT
943
943
11U1
1181
1181
1181
1181
956
956
956
956
956
956
956
956
956
956
956
961
961
961
961
961
961
961
1158
1158
984
984
984
984
0
HAUL
DISTANCE
2.37
2.37
1.69
1.69
1.69
1.69
1.69
3.05
3.05
3.05
3.05
3.05
3.05
3.05
3.05
3.05
3.05
3.05
3.30
3.30
4.30
3.30
3.30
3.30
3.30
2.59
2.59
3.24
3.24
3.24
3.24
0.00
NEIGHBOR-
HOOD TYPE
2
2
3
3
3
3
3
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
3
3
3
3
3
3
0
HAYS TO
COLLECT
TUEEk i
WEDS AT
MONTHU
TUEERI
rtEDSAT
MONTHU
TUETKl
WEDSAT
MONIHU
TUEFRI
WEDSAI
MONTHU
TUEERI
WFDSAT
MUNTHU
TUEEKl
WEDSAT
MUNTHU
TUEERI
WEDSAT
MONTHU
TUEERI
WEUSAT
MONTHU
TUEERI
WEDSAT
MUNTHU
TUEf-RI
wtDSAT
MONTHU
TUEI-R I
WEDSAT
TABLE 5-ID
-------
-81-
IN THIS RUN THERE IS A TRANSFER STATION WHERE THE
COLLECTION TRUCKS BRING THEIR LOADSt THE SOLID WASTE IS
TRANSFERRED TO 75 CUBIC YARD TRAILERS AND CARRIED IM
THESE TRAILERS PULLED BY TRACTORS TO THE FINAL DISPOSAL
SITE. THE TRANSFER STATION IN THIS RUN HAS A CAPACITY
OF 290 TONS PER DAY AND REQUIRES AN INITIAL INVESTMENT
OF 4428000.00,THE FINAL DISPOSAL SITt IS AT COORDINATES
FX «-39600., FY = 39000. THE TRANSFER STATION IS AT CO-
ORDINATES, TX = 66000., TY = 39000. THE DISTANCE FROM
THF TRANSFER STATION TO THE FINAL DISPOSAL SITE IS 20.0
MILES. 5 TRAILERS AND 2 TRACTORS WORK OUT OF THE
TRANSFER STATION.
THE MAP TITLED fMAP FOR SIMULATION RUN 23 SHOWS
THE RESIDENTIAL AREA DIVISIONS AND THE LOCATIONS OF THE
TRANSFER STATION AND THE FINAL DISPOSAL SITE. THb RUN
HAS SIMULATED ONE WEEKS OPERATION, AND THE RESULTS ARE
SHOWN BELOW.
1. COST OF COLLECTION TRUCKS OPERATION ... 13663.19
2. COST OF TRANSFER STATION AND
TRAILER TRACTOR OPERATION ... 23/1.00
3. TOTAL COST OF WEEKS ACTIVITY 16034.19
4. TONNAGE COLLECTED IN WEEK 1535.48
5. DOLLARS PER TON COST FOR COLLECTION
TRUCKS OPERATION ... 8.90
6. DOLLARS PER TON COST FOR TRANSFER
STATION AND TRACTOR OPERATION ... 1.54
7. DOLLARS PEK TON FOR ENTIRE WEEKS WORK ... 10.44
8. COLLECTION TRUCK TRAFFIC MILEAGE 1826.9
9. COLLECTION TRUCK NEIGHBORHOOD MILEAGE ... 2024.7
10. TRAILER TRACTOR TRAFFIC MILEAGE 1920.0
TABLE 5-iE
-------
-82-
11. NUMBER OF COLLECTION TRUCKS GETTING
ONE HOUR OF OVERTIME DURING WEEK
12. NUMBER OF COLLECTION TRUCKS GFTITNG
TWO HOURS OF OVERTIME DURING WEEK
13. NUMBER OF TRUCKS GETTING MORE THAN
TWO HOURS OF OVERTIME OURING WEEK
14. THERE WERE 1 BREAKDOWNS OR FLAT TIKES ON
COLLECTION TRUCKS DURING THE WEEK.
15. THE COLLECTION TRUCKS MADE 412 TRIPS DURING
THb WEEK.
16. THE TRAILER TRACTOR RIGS MADE 48 TRIPS
DURING THE WEEK.
AVE SIG MAX MIN
17. TIME IN MINUTES
IN DISPOSAL 7.74 3.85 25.LHJ 2.00
18. PERCENT TIMF SPENT BY COLLECTION TRUCKS
IN COLLECTING... 57.9
IN TRAFFIC 14.2
IN DISPOSAL .... b.l
OFF ROUTE 22.8
AVE SIG MAX MIN
19. HOURS IN WORKDAY 6.5 1.3 12.8 4.1
TABLE 5-1F
-------
-83-
20. PERCENT OF TIME THAT
STATION QUEUES WERE
TRANSFER
NO
ONE
TWO
THRFE
FOUR
FIVE
SIX
SEVtN
EIGHT
NINE
TEN
TRUCKS
TRUCK
TRUCKS
TRUCKS
TRUCKS
TRUCKS
TRUCKS
TRUCKS
TRUCKS
TRUCKS
TRUCKS
MORE
QUEUE 1
57.27
29.95
10.58
2.16
0.03
0.00
0.00
0.00
0.00
0.00
0.00
0.00
QUEUE 2
64.57
27.92
7.05
0.44
0.00
0,00
0.00
0.00
0.00
0.00
0.00
0.00
21. MAXIMUM LENGTH OF QUEUE IS
22. RESUME OF WEEK
DAY WEIGHT COLLECTED
IN TONS
MONDAY
TUESDAY
WEDNESDAY...
THURSDAY....
FRIDAY
SATURDAY....
298.55
296.16
282.69
220.88
220.22
216.99
COST OF DAY
IN DOLLARS
3026.00
3043.15
3016.87
2324.62
2354.lb
2269.40
TABLE 5-1G
-------
-84-
23. NUMBER OF TRIPS BY TRAILERS
TRAILER
TRAI
TRAI
TRAI
TRAI
LE*
LER
LEK
LER
71
72
73
74
75
MADE
MADE
MADE
MADL
MADE
1
1
I
1
3
1
1
0
3
TRI
TRI
TRI
TRI
TRI
PS
PS
PS
PS
PS
OUR
OUR
DUR
OUR
DUR
I
I
I
I
1
NG
NG
NG
NG
NG
WEEK
MEEK
WEEK
WEEK
WEEK
24. NUMBER OF TRIPS BY TRACTORS
TRACTOR 51 MADE 25 TRIPS DURING WEEK.
TRACTOR 52 MADE 23 TRIPS DURING WtfcK.
25. NUMBER Uf- TRACTORS GETTING ONE
HOUR OF OVERTIME DURING WEEK 3
26. NUMBER OF TRACTORS GETTING TWO
HOURS OF OVERTIME DURING WEEK 2
27. NUMBER OF TRACTORS GETTING MORE
THAN TWO HOURS OF OVERTIME a
TABLE 5-1H
-------
-85-
LIMITATIONS
General limitations in a single run of Model 3 are:
(1) only one transfer station can exist, although its location
can change with different runs.
(2) only one final disposal site can exist, although its
location can change with different runs.
(3) only one size of collection truck and one size of haul
trailer can exist, although the two sizes can be changed
with different runs.
SIMULATED SYSTEMS
A single run of Model 3 can be made with one of three simulated systems;
the decision as to which rests with the investigator. These are:
(1) Model 3A . Collection trucks make neighborhood collections
and then take their loads to a final disposal site.
(2) Model 3B. Collection trucks make neighborhood collections
and take their loads to a nearby transfer station with a suf-
ficient number of unloading spaces so that there are no
collection truck queues. Tractor-trailer rigs then carry the
solid waste from the transfer station to the final disposal site.
-------
-86-
(3) Model 3C. Collection trucks make neighborhood collections
and take their loads to a nearby transfer station with two
unloading spaces, so that at times queueing exists. Tractor-
trailer rigs carry the solid waste from the transfer station to
the final disposal site .
SEVEN POLICY DIVISIONS
The most important control exercised by the investigator is that of which
these three systems will be simulated. Policy decisions must be made also
for:
(1) The extent of urban area to be investigated:
This decision will normally be based on considerations other
than model limitations. This report investigates the Northwest Division
of the City of Baltimore, an area delineated by the Baltimore Bureau of
Sanitation as one of four into which the City is divided, and the one from
which collection is most expensive . Its area is approximately 20 square
miles. The only constraints on size of the subject area in the model is
that it must require no more than 50 collection trucks in the field per day;
it must lend itself to division into no more than 25 subareas, each of con-
stant neighborhood type; and no more than 10 tractors and 20 trailers must
be required to operate from its transfer station .
-------
-87-
(2) Frequency of Collection:
The model operates for either semiweekly or triweekly
collection policy.
(3) The size of the collection trucks:
Any size truck may be used in the model; size is expressed in
net loaded pounds, not cubic yardage. However the structure of the model
generates a daily assignment of household units taken from Model 1 results
for the larger 20 cubic yard trucks. The smaller 13 cubic yard trucks in
general gave responses which indicated their assignment capability was
about 0.85 to 0.95 of the larger trucks. Simulation runs with the smaller
trucks must set the correction factor ASSUNK to 0.90 to reflect this
reduced potential .
(4) The size and type of the transfer trailers:
The model will accept any capacity trailers; the system constraints
are the state motor vehicle laws. The trailer length limitations appear to
govern more often than weight limitations unless auxiliary compaction of
the material is carried out at the transfer station .
(5) The transfer station site and routes between it and the subareas:
The model will accept any location within or beyond the urban
area being investigated.
-------
-88-
(6) The final disposal site and the routes to it:
In Model 3A, the collection trucks make the haul to the final
disposal site. For this model, if the urban area is very large, i.e., of the
order of 300,000 population, the site must be correspondingly close that no
more than 50 collection trucks are required; also, the route for no truck can
exceed a distance of 24 miles. In Models 3B and 3C, the tractor-trailer
rigs make the haul to the final disposal site; for these models, there is no
distance constraint other than that the site must be sufficiently close that
no more than 20 trailers or 10 tractors are required for the transfer station
operation.
(7) Overtime pay:
The user has the option of paying or not paying overtime.
SYSTEM DATA REQUIREMENTS
These seven operating decisions above complete the system's policy decisions.
The investigator, in addition to the above, must use the values in the present
program, or supply other more applicable data, for the following: Distribu-
tions which reflect collection rates in pounds per hour for different conditions
of neighborhood type and days of accumulation of waste, collection trucks'
dumping times, trailer dumping times, number of household per acre by
neighborhood type, and pounds of waste generated per capita per day.
-------
-89-
Regression equations of traffic velocity on traffic distance are in the model
with coefficients of which can be changed in the data block. The standard
error of estimate used with these equation can be changed also. Equations
are present in the model which give as dependent variable the number of
housing units to be assigned to collection trucks. The haul distances in
miles are the independent variables, and three 2-dimensional matrices list
the equation coefficients as functions of neighborhood types and collection
frequency per week . These coefficient values can be changed in the data
block if desired .
Also, values must be decided for data; the values used in the runs of this
study are shown in parentheses.
(1) The average number of persons per housing unit for each
neighborhood type; (2.7, 2.9, 3.1, 3.4)
(2) Amortization time period and interest rate for transfer station
structures and appurtenances; (30 years and 10%)
(3) Capital investment in transfer station land; (varied with station
size, but ranged from $40,000 to $80,000)
(4) Ratio of gross acreage to net acreage by neighborhood types;
(1.3, 1.4, 1.6, 1.9)
(5) Hourly operating cost for collection trucks; ($4.40)
-------
-90-
(6) Hourly operating cost for tractor-trailer rigs; ($11 .00)
(7) Minimum off route time to be charged to truck crews: (50 minutes)
(8) Driver and laborer daily pay scales; ($20 .00 and $18 .00)
(9) Amount of tax revenue lost from city's use of transfer station
land rather than private use of it; (none, as use was of land which
would otherwise be park)
(10) Monthly utility cost of transfer station; ($100)
(11) The frequency of truck breakdowns or flat tires, and the off-
route time to be charged in such event; (one every 1000 traffic
miles)
STRUCTURE OF MODEL 3
The list of processing programs prepared by Dr. Mandell Bellmore again was
used in this model . A MAIN program served as the focal point out of which
the operating subroutines were called . The structure of the model may be
thought of as being divided into three blocks as shown in Figure
5-1 .
The dictionary in MAIN is in two parts, one for list processing terms, the
other for the simulation variables. BLOCK DATA has been described in
Chapter 3 .
-------
-91-
MAIN Program with
complete dictionary
BLOCK Data
(1) Model accepts policies for
run; initializes variables to
proper values and carries out
many calculations for truck
assignments by days of week .
Tables I and 2 are listed .
(2) Simulation of six day1 s
activity is made with summaries
of system responses at the end
of each day.
(3) Summary of the entire week's
activity is made. Applicable
calculations are carried out.
System responses are listed .
FIGURE 5-1. General Schematic of Model 3
-------
-92-
Block 1 of Figure 5-1 serves as a necessary preface to the actual simula-
tion of the weeks operations of solid waste collection and eventual
transport to a final disposal site . Five subroutines are called by DRIVER.
These read specific run data as which of the three systems is to be used,
i.e., Model 3A, 3B, or 3C, collection frequency, etc.; the many variables
are initialized to proper values; the traffic distances from the subareas are
calculated; the number of households to be assigned to each truck each
day of the week is calculated, and the total number of trucks for the system
is found; trucks by number are assigned to routes in subareas by number for
each day of the week. The daily cost of the transfer station is calculated .
A paragraph which describes the conditions for which the run is being made
is printed; Tables 1 and 2 are printed .
Block 2 of Figure 5-1 is structured within an "1 = 1, 6" loop, which for the
six days of the week sequentially does the following:
(a) Calculates the route number for the trucks for the day of the
week. If triweekly collection frequency is being simulated,
Monday, Wednesday, and Friday work covers Route 1;
Tuesday, Thursday, and Saturday work covers Route 2.
Three routes per week exist for semiweekly collection .
(b) Calculates the total number of trucks to be fielded for the
particular day. This is not constant throughout the week.
-------
-93-
(c) Calls TIMER subroutine which, in turn, call subroutines which
initialize to zero those variables which must be initialized
at the beginning of each day, starts trucks on their tasks, and
coordinates and records their activities until the day's end .
TIMER also controls and records the activities at the transfer
station. Finally Block 2 calculates the simulated costs of the
day1 s operations.
Block 3 processes system1 s responses for the entire week by making necessary
calculations and calling statistical subroutines. The latter includes formats
and commands for result listing.
Figure 5-2 shows a more detailed interaction of the MAIN program with
the subroutines. The three blocks of Figure 5-1 again are delineated . A
discussion follows concerning individual subroutines positioned in Figure 5-2.
BLOCK 1 SUBROUTINES
(1) RUNDAT: Gives command to read run values for:
(a) COLFRE, collection frequency: may be 2 or 3.
(b) ASSSUN, value of 0. causes simulation of Model 3A;
value of I. causes simulation of Model 3B;
value of 2. causes simulation of Model 3C .
-------
-94-
SINVd B 'XNH'IIJ 'iSVTId '1SJTIJ '1STW3H '1SJH3M
'X1HOOI SV H30S S3NlinOH8nS Ailllin e 9NISS30OMd iSIT
en
01
3
o
3
CO
CM
O
U-l
O
c
o
•H
4J
O
CX)
0)
•U
ti
-------
-95-
(c) ASSUNK, a control variable: normally equal to one. The
number of household units assigned to any truck is equal to the
product of ASSUNK and the number of household units generated
by the regression equations.
(d) TRLHAL: the distance from transfer station to final disposal
site in miles.
(e) RUNNO: run number.
(f) K: random number generator seed .
(g) NOTRC: number of tractors at transfer station if given a value
of a positive integer; if given a value of zero, the program cal-
culates a NOTRC value from a deterministic equation which
has trailer haul distance, collection frequency, trailer capacity,
population served, and average weight generated per day per
person as independent variables.
(h) Q9, a control variable, when equal to zero no overtime is paid
to collection truck crews; when equal to one, overtime is paid.
(i) Q10, a control variable which is set equal to 1 if collection
truck traffic distance is to be calculated from coordinates. If
Model 3A is being run, it may be set equal to zero which will
set all collection truck traffic distances equal to a constant
value, e.g., TRLHAL.
-------
-96-
(2) ZERINT: Initializes most variable values to zero; sets all tractors to
"idle and empty" status; puts first trailer in "being loaded" status.
(3) TABL 1: Calculates haul distances from each subarea to the collec-
tion truck's dumping destination, and calculates number of households
which comprise a daily truck task for each of the subareas. Calculates
the number of truck routes in each subarea.
(4) TABL 2: Calculates total number of collection trucks in the model;
assigns trucks by number to areas by number for each day of the week;
calculates each truck's attributes of haul distance, neighborhood
type, and size of assigned task; calculates size, capital investment,
and number in labor force at transfer station; calculates daily cost
of transfer station from the sum of the following costs: labor, land,
utilities, appurtenances and structures, and loss from tax revenue not
realized .
(5) TBLPRN: Gives formats and commands for printing lead paragraph
which describes the system being simulated and formats and commands
for Tables 1 and 2. Table 1 lists the subareas and their attributes.
Table 2 lists each truck and its attributes such as assignments, haul
distances, subarea in which it is to work, etc ., by days of the week .
-------
-97-
BLOCK 2 SUBROUTINES
Many of these are list processing or utility types and serve the identical
function in Model 3 as they did in Models 1 and 2. Reference is made to
Chapter 3 in which descriptions are given of the following subroutines
common to all three models: TIMER, CAUSE, CREATE, FILFST, FILAST,
FILRNK, IDCHK, PACK, REMFST, UNPACK, CLOCK, HIST, RANDOM,
RANDER, and SSWTCH. Subroutine STAC is identical with Model 2 STAT .
(1) DAYSUM: Calculates separately each day1 s costs of collection
trucks activities and of transfer station tractor-trailer operations.
(2) XINIT: Initializes list processing variables to proper values.
(3) INIT1: Initializes to zero each morning those simulation variables
which have had their values changed during the preceding day's
operation .
(4) DATMAK: Fields the trucks at the beginning of each day and records
their movement into traffic in the list processing subroutines.
(5) TRAFIC: Records each collection truck's accumulative time and
distance in traffic, both to and from the collection area. Possibility
of flat tires and breakdown is included.
(6) COLECT: Generates number of miles that each truck covers while
collecting; generates a different collection rate for crew for each
-------
-98-
Irip to collection neighborhood; generates total weight to be
collected by each truck for each day; notes when day's task is
finished for each truck, and accumulates total time spent in
collection .
(7) RIGOUT: Counts number of trips for trailer-tractor rigs, for
trailers separately, and for tractors separately; generates dumping
time at final disposal site from a normal distribution; generates
traffic speeds and elapsed times in traffic both to and from final
disposal site; records actual operating time of rigs for cost cal-
culations.
(8) RIGBAK: Checks and records when trailer-tractor rigs are on over-
time; determines if a full trailer awaits the returning tractor, and
if so, combines them and dispatches them .
(9) DISPSL: Notes whether Model 3A, 3B, or 3C is being simulated;
generates dumping time from histogram; directs truck to shorter of
the two queues when applicable; records total number of collection
truck trips; notes if trailer becomes full and replaces it with an
empty one when applicable; dispatches full trailer to disposal site
if tractor is available, otherwise sets its status to "idle and fuM",
notes overtime for collection trucks at end of day, notes when quit-
ting time permits truck servicing and records off-route time for this
activity.
-------
-99-
BLOCK 3 SUBROUTINE
(1) WEEKSM: Sums the six days of collection truck's costs to give the
week1 s total; sums the six days of transfer station trailer-tractor costs
to give the week's total; calls statistical routines for calculations
of desired output; summarizes queueing operations.
(2) FNLPRN: Lists formats and commands,switching as needed for
Models 3A, 3B, and 3C .
-------
-100-
LOGIC FLOW CHARTS
Five subroutines of prototype activities have been described; they are
TRAFIC, COLECT, DISPSL, RIGOUT, RIGBAK . Their logic flow charts
are presented in Figures 5-3 through 5-7.
MISCELLANEOUS ASSUMPTIONS
LIMITATIONS, AND COMMENTS ON MODEL THREE
(1) Collection frequencies other than semiweekly or triweekly cannot be
simulated on the model; this reduces its general applicability as simulation
of once-weekly or daily systems are eliminated .
(2) In TRAFIC and RIGOUT subroutines, the truck and tractor speeds are
drawn from a normal distribution which has as mean a val ue taken from a
regression equation of log speeds on trip distances. The coefficients of
these equations and the standard deviations of the distribution can be changed
by changing their values on data cards. Maximum and minimum values for
these speeds can be varied equally easily. The form of the equation is
within the program however, and coding change would be necessary if
another type of equation is desired .
-------
TRAFIC CALLED
BY TIMER
YES
TRFDIS(NT).GT. RM X DST
NO
VELMU - VELMUT
VELMU •
RKA +RKB*TRFD!S
CALL RANDM(VELMU.VELSIG, TVELOG)
1 '
TRFVEL«IO*-*TVELOG
YES
NO
_L
TRFVEL.LE. VELMAX?
< TRFVEL.6T. VELMIN ?
YES
NO
TRFVEL=VELMAX
L
I
ITRFVEL «VELMIN \
[ TRFTMZ - TRFDIS(NT)/TRFVEL* 60 ]
[TRAFTM(NT) -TRAFTM(NT) + TRFTMZ]
I
[RND= RNNR(0) |
I
[FLATNO * PRBFLT x TRFDIS(NT) |
I :
YES
RND.GT. FLATNO
NO
TIME(NT) • TIME(NT)
+TRFTMZ
| OR(NT) -OR (NT) 4- FLTLTM |
i ""
TIME(NT) = TIME(NT)
+ TRFTMZ -»-FLTLTM
YES s~
f<
1
EVENT(NT) .GT. 1 ?
NO
I EVENT (NT) -4 |
| EVENT (NT) - 2
\ TRFMIL(NT) -TRFMIL(NT) +TRFDIS(NT)
RETURN
FIGURE 5-3
-101-
Subroutine TRAFIC, Model 3
-------
-102-
(COLLECT [
I
NETYP • TNETYPINT, NOR)
YES
NO
200
f
| RND'RNNR(O) * 100 j
N3N • DSLC -1.
,- 1 GO TO (271, 272, 273, 274), NET YP|
_2_
2
2
2
- — -( GO TO
^— -j GO TO
(281 , 282,283 ), N3N [— "i
(284, 285, 286
), N3N [-•
73 »| GO TO (287, 288, 289 ), N3N |—
M »| GO TO
(290, 291 , 292 ), N3N J— -
-,
Z°'H CALL
HISTIHISC 1 2, RND, Y ) (— -,
i i^ CALL
1 ">j CALL
h— H CALL
285 i
• *\ CALL
-^ij CALL
HISTIHISC 13 ,RND, Y ) [— .
HISTIHISCI4.RND.Y) |— •
HISTIHISC 22, RND.Y ) |—
HISTIHISC 23, RND.Y ) f—
HIST 1 HISC 24, RND, Y ) (— •
— -^ CALL HIST (HISC 32, RND.Y ) (— H
288 i
-ii^j CALL
HIST(HISC33,RND,Y) 1— •!
„ _ _
.[ CALL
HIST(HISC34,RND,Y) (—
" •[ CALL HIST ( HISC 42, RND, Y ) | — •*
— — *\ CALL HISTIHISC 43, RNO, Y ) (—J
nnr.
^— ~\ CALL HIST (HISC 44, R
100
| TRIP(NT) • 1 |
[ RND • RNNR(O) X 100. |
,
J — | GO TO (202, 204,206,208), NETYP j
«| CALL HtSKHISTUI ,RNO,Y)J 1
»j CALL HIST(HISTL) 2, RNO, Y) J— .
•) CALL HI ST(HISTU3, RND.Y) | — i
' ^ CALL HIST (HISTU4, RNO, Y) | •
210
•
to
»
»
| UNACRE • Y |
-
ACRE-TNOHUNINT, NDR)XCORACR(NETYP)
/UNACRE
.
CALL RANDOM ( PN DM U. PNDSIG. PNDPE R) 1
~
r
WATE (NT) - PE RUN (NETYP) X PNDPE R
*DSLCXTNOHUN(NT,NDR)
1 WT * WT + WATE (NT)
i
i
SCOLML • SCOLML -f
(ACRE X COL ML K I NETYP)/ 5280.)
295
\
COLRAT-T"!
--
[ TTT- TOTWTINT) +WATEZ |
/TTT'
E\TTT J
| TTT2-TTT 4- IOOO. |
710
<^TTT2i
WflTT i WT 1 ? ^V-""v .,.
\
WATE(NT) ?>-22 ,
\
| TOTWTINT) • TOTWTINT) + WATEZ |
..
| TRKLDINT )= WATEZ |
4OO
| TRKLDINT) -WATE(NT)- TOTWTINT)
I
| OOINT) • 1 J
(7?0 f '
[ EVENT (NT) • 3 |
__-
COLTMZ-ITRKLOINTIM 6O./COLRAr)
| TIME(NT)-TIME(NrH-COLTMZ |
I COLHR • COLHR +COLTMZ I
FIGURE 5-4
Subroutine COLECT, Model 3
-------
-103-
TIMEQH 0,1) -TIMEQ(LO.I) +
FLOATIITIMEI-ITIMLILO.n)
I
T1MEQ(LP,1)-TIMEQ(LO, 11 4_XIC
FIGURE 5 - 5A, Subroutine DSPOSL, Model 3
-------
-104-
A a
c- * *
f ^^X^WU 1 M 1 J 1 ^f
f
(QUITTMINT, JOW)-CLKTM|
J
|K3TRK -0|
<^CLKTM S 480?^>
i
| OVRRTMZ * (CLKTM -4 801/60. |
|
| JOVRTM -OVRTM |
|
| OOVRTM • JOVRTM |
J™^
| OVRTM (NT) • JOVRTM +1 | f OVRTM (NT)- JOVRTM |
| jinn J
t §
| JKLM = OVRTM(NT) |
J
NO .," -^ ••%. YES
i ^s« * ^ ^^~ i n
IT T
I — (GO TO (77,78) JKLMJ |NOVRT3= NOVRT3-t-l| | ORTM = (480. -CLKTM)/2.| [ EVE NT (NT) > i j
77 ' '
79
^NOVRTZ^NOVRT 2 4- l(— »
t
* 1 «
| RIGLOD- RIGLOD f TRKLD(NT) |
<^mrt nn < niruay ?>>
#
| RIGLOD = 0 |
1
| /r-r-
^X^"CTA T ( 1 ) " 1 3 ? '^S.
Ann f~ "^^. • -^ 1
*•" T '" *
I 1
[ PRINT "SUBROUTINE DSPOSAL NOT OPERATIVE" J | STATIJTRL ) • 12 |
,, . J
1 "^oTATl I)-10r^>
301 |
1 CONTINUE |
| PRINT "SUBROUTINE DSPOSAL NOT OPERATIVE" |
[ STOP"]
)« CLKTM
247
I)" 13 1
FIGURE 5 - 5B
Subroutine DSPOSL, Model 3
-------
-*\ DO 321J*51, NOTRC2 |
321
909
CONTINUE
|TRC(J) =J |
|TRL(J)= JTRL |
'
| STAT(J) = 9 |
JSTAT(JRTL) =• 11
^
|K2RIG = l|
NO
K2RIG 8 K3TRK =
YES
K3TRK = 0?
NO
999
NO
1
[CALL CREATE (4, IDNOZ) |
| 1TYPE2 = EVENT(NT) + .5 |
HTIMEZ = TIIVIE(NT) -t-.Tl
i
ICORE(IDN024-3) = NT|
I
LCALL CAUSE (ITYPEZ.IDNOZ,
I NT - J | 1001
[ EVENTtNT)'?]
ITIME(NT) =CLKTM + 5.
LLI
-105-
YES
1NDAY=99
RETURN | 1002
I
END
FIGURE 5 - 5C
Subroutine DSPOSL, Model 3
-------
-106-
| RIGOUT |
("TRPRIG'TRPRIG + 1
i ~
| JTRL'TRL(NT) |
JTRC=TRC(NT)
'
_
TRIP(JTRL) 'TRIP(JTRL)+l|
CALL RANDOM(ONCE. TRES, RDPTM) ]
I
[VELMU' RKA + ( RKB * TRLHAL )J
«
1
I VELMU = VELMUR
*
CALL RANDOM(VELMU, VELSIG, RGLOG 1 )
I
CALL RANDOM(VELMU, VELSIG. RGLOG 2 )
I RGVLI * 10** RGLOGl]
* ... *
RGVL 1 = RGVMIN
IIJU,x^nnvi i •*• RfivMAy 7r
RGVLI = RGVMAX]
S.YES
i 1
RGVL2 =
RGLOG 2
, ?i°
ff
RGVL2 •= RGVMIN] (
T
1
[RGVL2 =
»
...'^^ 1
M Q 1
wi- r*
" w ^nc\j\ ° •*• nrv/MAY P'^s,, ' *~**,
RGVMAX |
*
MGONE = RDPTM + (TRLHAL * 60. /RGVL) )
+ (TRLHAL*60./RGVL2)
X
EVENT(IMT) = 8
[ TIME(NT)^TIME(NT) + TMGONE |
[TRL(NT=JTRL~]
| TRC(NT) = JTRC~|
I
_
I OPTM(JTRC) = OPTM ( JTRC) + TMGONE
(NT) =TRIP(NT)
RETURN
FIGURE 5-6
Subroutine RIGOUT, Model 3
-------
-107-
IRIGBAK
| FIN DAY'"
--
I KBAK :TIME(NT)+0,5|
| JTRC = TRC(NT) + 0,5 j
| STAT( JTRC)« 8 ]
( JTRL= TRL(NT)+0.5 |
' '
I STAT(JTRL) " 10 |
i
[ QUITMCtJTRCHKBAK |
i
[ XI01=QUITMC (JTRQ-Q8
XI01< 480?
I X II I=X 111- 8.0 [
X 11 1 + 1 . 0
M3>2?>
YES
GO TO(80I, 802), M3
801
802
|B(3)*B(3)
|B(2)°B(2) -f
-^ 1
1
NO
•j DO 10 1 » 71, 90J
J°_L
STAT(I)=
YES
CONTINUE J
20
DO 35 J' 51, NOTRC2)
10
CONTINUE
X
[FINDAY =99
I EVENT(NT)-7 |
i
| TIME(NT) " KBAK + 10 )
| TRL(NT)° I |
I
TRL(NT)
I
JLL
[STAT(NT) » 9 |
[ STAT(l) "ll|
'
RETURN
FIGURE 5-7
Subroutine RIGBAK, Model 3
-------
-108-
(3) In COLECT subroutine, the assumption is made that the collection
truck returns to disposal site or transfer station only when a particular
truck capacity has been exceeded or when the loaded weight, even though
less than capacity, completes the day's assignment. Thus Model 3 assumes
a greater efficiency in system operations than did Model I which, based
on field observations, drew from a histogram to determine "loaded weight".
(4) In RIGOUT subroutine, the time spent by the trailer-tractor rig at the
final disposal site is drawn randomly from a normal distribution based on
field data for such rigs. The distribution parameters may be changed easily
with data cards, but program coding changes would be required to change
the type of distribution .
(5) An empirical equation for setting the number of tractors at the transfer
station is in RUNDAT . If NOTRC is set to zero on the run data tape, the
equation is used; if NOTRC is set equal to any positive integer, the
program by-passes the equation, and the number of tractors at the transfer
station is that value given NOTRC . The equation is discussed below:
Let N = number of tractors needed .
NL = maximum number of trailer loads per day trans-
ported to disposal site .
-------
-109-
LPTPD = loads per tractor per day.
SUMUNIT = total number of household in the complete
area under study.
AVP = approximate number of persons per household.
COLFRE = collection frequency per week.
DSLC = maximum days since last collection;
4 if COLFRE =2, 3 if COLFRE = 3.
RIGMAX = pounds capacity of trailer.
TRLHAL = one way distance in miles between transfer
station and disposal site .
The equation development follows:
(a) N = KIL/LPTPD
SUMUNIT * COLFRE * PNDMU * DSLC * AVP
where hIL =
6 * RIGMAX
and LPTPD = 6.9 - (O.I * TRLHAL).
This latter equation approximates the number of trips possible per
day for a tractor; it is deterministic using average speeds and
average time at disposal site. It is for a no-overtime day.
Equation (a) is thus:
SUMUNIT * COLFRE * PNDMU * DSLC * AVP * 10.
N =
6. * RIGMAX * (69. - TRLHAL)
-------
-110-
The value of N is integer. The coding constrains the answers between 2
and 10 inclusive; the former as it is believed that proper planning would
require more than one tractor regardless of the smallness of the station; the
latter because of model limitations.
(6) The number of trailers assigned to the transfer station is determined
only by the need. The program calls additional trailers as needed up to
a limit of twenty, beyond which the model is inoperative. Successive runs
under constant conditions may require different numbers of trailers because
of stochastic influences.
(7) Production runs in this study were made on a particular quadrant of
Baltimore city. The description of this tract is in format statement 8022
of TBLPRN subroutine. If the investigator wishes to incorporate a descrip-
tion of his tract, the proper description format should replace the existing
8022 statement, but should retain the number. If no such description is
needed in output, the card commanding this format, "WRITE (IOU, 8022)",
line number 2210 of TBLPRN, should be removed.
(8) If auxiliary compacting apparatus is to be simulated at the transfer
station, two card changes are needed in the data: RIGMAX must be
-------
-Ill-
changed to reflect the increased trailer load and COMPAP must be
changed from a value of zero to a dollar value of the material cost plus
the installation cost of the compacting apparatus.
(9) Subroutine TABL1 calculates collection trucks' haul distance from
a subarea (I) either to the transfer station, when it exists, or to the final
disposal site. The program coding is such that one of three distances
may be used at the option of the user. These are:
(1) A linear distance along a well traveled thoroughfare which
would be used regularly from the population centroid of the
subarea to the dumping site . Its length in feet is entered in
data as ROADIS(I).
(2) No such thoroughfare may exist, and the user may believe
that trucks from the subarea will travel many different routes
to and from dumping, all within the framework of a city's
rectangular street system. In this case, ROADIS(I) is set to
zero. AX1(I), AX2(I), AY1(I), and AY2(I) are given values
other than zero, and the subroutine calculates haul distance
from the equation
ABS [AX 1(1) - AX2(I)J + ABS [AY1(I) - AY2(I)J .
-------
-112-
In the above, AX 1(1) and AY1(I) are the population centroids
of subarea (I) in a rectangular grid of the urban area. AX2(I)
and AY2(I) are grid coordinates of the dumping site . This
[AX+AY ] is often used for travel distance in city planning;
it is termed the "metric L". The units of the grid are feet.
(3) The user may assume truck movement along part of the route
by metric L path and part along a defined measurable path.
In this case, an equation incorporating both distances is
used. Table 6-1 illustrates data for Model 3 runs for all three
procedures.
The equation in subroutine TABL1 which generates the assign-
ment of number of households is:
XiO) =q + K2 * x2(i)i + tc3 * x2(i)2]
in which:
I . X], (I) is the number of household units from a subarea (I)
which constitute a single truck's daily collection assignment
2. X2(l) is haul distance from subarea(l) to the dumping site.
3. GI , C2 , and C3 are equation coefficients obtained from
three matrices of values, Cj: in which "i" is neighborhood
type, and "j" is collection frequency. These values are
from regressions using Model 1 responses.
-------
-113-
(10) Subroutine TABL2 calculates total capital investment in the trans-
fer station by summing land value and cost of structures and appurtenances.
The transfer station expense is reflected in interest charges on the land
value, by depreciation charge on the structure and appurtenances, by
loss of tax income from the land when applicable, by utility charges,
and by station labor expense . In the discussion below, the program coding
variables and their values in this study are given .
The land values are as shown below. Station capacity in tons per day
is "C".
When Land value
C ^200 CONA
C > 200 C * CONF
CONA = $40,000
CONF = $200/ton
The cost of structures and appurtenances are as shown below.
When Cost of structures and appurtenances
C L 100 COND
C > 100 CONB + (C * CONE)
COND = $125,000
CONB - $ 75,000
CONE = $500/ton
-------
-114-
The cost of auxiliary compaction equipment is added to the cost of the
structures and appurtenances. This variable, COMPAP, has a value of
$150,000 in this study when this apparatus is in use . The value will be
zero for all users when the apparatus is not in the system.
The depreciation term, YRS, has a value of 30 years. The interest rate
variable, R, is 10% both for land investment interest and for structure
amortization . This reflects a rate of return proper for other public bene-
fits which remained unbuilt rather than reflecting municipal bond rates.
A three man crew is assigned to the transfer station when capacity is
below 200 tons per day; a four man crew when greater.
-------
-115-
CHAPTER 6: RESULTS FROM MODEL 3
Model 2's great limitation is that the urban area being investigated must
be of constant neighborhood density. Model 3 does not have this limitation
and can investigate model responses from simulated systems in actual urban
areas composed of tracts of different neighborhood types. This study has
used the northwest quadrant of Baltimore city for its investigation. The
area has approximately 757000 housing units, 225,000 population, and was
divided for this study into thirteen subareas, each of a particular neighbor-
hood type.
Figure 6-1 is a sketch of this portion of Baltimore; the divisions into the
subareas and the simulated location of the transfer station are shown.
Table 6-1 tabulates the properties of the subareas gathered by the
investigator as first step in using Model 3. The information in Table 6-1
was given to the model, which then processed it and used it as basis for
calculations for number of needed collection trucks and in their assign-
ments to subarea routes. Thirty-one runs were made with Model 3 for
this study. The tabulation of the policies and environmental conditions
of the runs is presented in Table 6-2. The runs were made for investiga-
tion of the following:
-------
-116-
I . Proving the model
2. Noting model responses to interactions of varying collection
frequencies and haul distances with and without transfer station.
3. Determination of critical distances beyond which the use of a
transfer station is economically feasible .
4. Cost of increasing collection in the area to triweekly frequency
with haul to present incinerators.
5. Effect on cost of auxiliary compacting equipment at transfer
station.
6. Sensitivity of costs to number of transfer station unloading docks.
7. Sensitivity of costs to number of transfer stations in the area .
8. Sensitivity of costs to tractor-trailer ratios.
9. Sensitivity of model responses to different random number sequences,
The results of the investigation follow.
-------
-117-
X = 50,000.
Y= 50,000,
r
J
X=66,000
Y = 39, 000
TRANSFER STATION
A
DIVIDED INTO 13
NEIGHBORHOOD TRACTS.
o
tr
FIGURE 6-1
Northwest Baltimore
Served with One Transfer Station
-------
-118-
UJ
Di
O
^p-
:§
1—
<
CO
1 1
0
1—
Z
C£
Q
<
0
1
p~"
i/>
UJ
X
H-
c£
O
7
S
O
Qi
u_
£
<
Q
<-
^<
UJ
Qi
3
CO
ID
CO
_
1
o
1 1 1
1
CO
1/1
5
0
ct;
CN
>
<
CN
*
*s.
u
CK:
i —
UJ
5 >
s _ <
^
>_ O M
Q} _C •*"
-Jd 0 c
i 3^
Zx
5
'•S ° 3 -
i CN p 0
.ro- S E
"> 'o U *-
0 ^
Q
"8
0
•£
•h ^
— in
-* ^t-
0 O
O 0
CN M-
*. S.
^ >0
in in
o o
§ §
^ •>
— m
^ ^t
0 0
o o
CN ^
*. S.
-* o
m in
— o o ^
— o o co
l\ O "3" -O
^ ». V *.
m •— — TJ-
< o o
— — CN
oo rx hs
CN CN CN
CN —
CN CO
o
o
o
o
CO
0
o
o
"*.
-o
o
o
8
V
CN
^t
0
o
CO
*.
CN
o
Tfr Os
CN l\
— o
s. s>
O CN
IX
rl
CN
CN
•<4-
-------
-119-
^
4—
o
I.I.J
ce
O
5
^-^
p
<
CO
u_
o
1 —
z
<
Qi
Q
<
O
h-
uo
LJJ
<=
^_
c*:
0
7
-<
•«£
O
Qi
U_
<
<
Q
<
LLJ
0£
^f
%
ID
CO
1
NO
LLJ
_J
CQ
<
OO
Q
<
O
Qi
CN
s_
x^
<
CN
_l *
-1 <
y
Ctl
1—
LU
2 r
S, <
*- (U
-° C
D
0) _C *-
^ 1 5
3 8
Z X
O
'•^ S " •/>
g ^ 1 o
o>^ g S
jj^Nj-
Q
"0
o
0
r( <*>
Q 0-
_Q >.
-C L^
.?
'5
Z
8-2
2 E
< D
Z
o
>-^i
5
*•.
CN
O O
o o
m o
oo o
CO CO
0 0
0 O
CN O
«. «*
CO NO
NQ NO
o o
o o
in ON
CxT CN^
CO CO
0 0
0 0
CN in
V N,
CO ON
NO in
•— o ON ON ix NQ Lnixco-^-ON-—
•— •— IXlXOOO NOoOONlX-NJ-O-
OONONOCN-— OOIX- rx ix Jx rv ix
CN CN ^^ CN CN
—
K
-------
-120-
•
g
^
LU
Q£
O
£
1—
<
CO
u_
o
t—
1
Q
<
D
0
1—
oo
yf
^
X
J—~
01
O
z
5
o
C£
u_
2
Q
<
LU
rv
<
03
Z3
to
^
O
LU
_l
CO
2
OO
Q
O
a:
CN
>
<
CM
_i X
<
(J
C£
t—
LU
_ si
C '^
O i- <
•Z jg
0 C
3 ,^
o° ^
X
<
^2
i- O in
Z x
Z
•— /— \ ,A
*- Si *^ WJ
gcf §-S
.2>r: 5 2
S ^ u •"
Q
-n
5
o
_f—
o g
-o >;
_c -T-
.?
*«)
Z
l_
n «
S -Q
2? E
^f -^
co co p
§ 0 C
S 8 g
CM _T „.
oo oo g
1 S §
co irT
CO CO ?5
§ 0 0
S 5? 8
S oo S3
jg Sc^^^g °5
co m -t o o of- 60
V «. S N X «.
— — — CN 10 CO
•— m so fv co CM
)
K.
>
)
I
»
>>
N. IN. CM ^ CS
OO CO CO K —
o so in -rf 10
— — •—•— o
CO Tf vQ IS.
CM CM CM CM
-------
-121-
c
o
JJ^
LU
Q£
O
•<.
•£.
i^-
<
CO
u_
o
1—
z
S
Q
O
1 —
V/1
LU
<:
X
t—
C£
o
7
5
0
Qi
LL.
<
<
Q
<
LU
f^S
O*_
<
CO
Z3
CO
_
1
o
LU
1
CQ
<
1
^ S S
S "0° "~
V
Q
"8
O
f"
>- (U
-D 1
^ ^
.5*
Q>
Z
si
S E
00 00
CM CM
o 2
o o
sO O
*. S.
•— o
K 0
IV CM OO •<* — iP —
— «o CN m co iv -*
o o in •— iv in iv
— CM — — O —
•— CM co ••* -0
IV IV O
— oo m
CO IV —
V *. **
CM — CM
R 0
in «n
CO
CO
"~
IV
CO
0
*.
CO
-------
-122-
TABLE 6-2
MODEL 3 RUNS
Run
No.
1
2
3
4
5
6
7A
7B
7C
7D
7E
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
Model
No.
3C
3A
3C
3A
3C
3A
3C
3C
3C
3C
3C
3A
3C
3A
3C
3A
3C
3A
3C
3A
3A
3A
3A
3A
3C
3C
3C
Collection Haul
frequency distance
2/week
2/week
3/week
3/week
2/week
2/week
3/week
3/week
3/week
3/week
3/week
3/week
2/week
2/week
3/week
3/week
2/week
2/week
3/week
3/week
2/week
2/week
3/week
3/week
2/week
2/week
2/week
24
24
24
24
8
8
8
8
8
8
8
8
16
16
16
16
4
4
4
4
9
9
9
9
4
16
24
Over- Corn-
time paction
paid apparatus
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
no
no
no
no
yes
yes
yes
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
yes
yes
yes
NOTRC
value
0
-
0
-
0
-
0
0
0
0
0
_
0
-
0
-
0
-
0
-
-
-
-
-
2
2
3
Transfer
stat ion
Y
N
Y
N
Y
N
Y
Y
Y
Y
Y
N
Y
\J
Y
N
Y
N
Y
N
N
N
XI
N
Y
Y
Y
-------
-123-
TABLE 6-2
MODEL 3 RUNS (cont.)
Run
No.
24
25
26
27
28
29
31
32
33
Model
No.
3B
3B
3C
3C
3C
3C
3C
3C
3C
Collection
frequency
2/week
3/week
2/week
2/week
3/week
3/week
2/week
2/week
2/week
Haul
distance
8
8
12
12
8
8
12
12
12
Over-
time
paid
yes
yes
yes
yes
yes
yes
yes
yes
yes
Com-
paction
apparatus
no
no
no
no
no
no
no
no
no
NOTRC
value
0
0
0
0
2
4
0
0
0
Transfer
station
Y
Y
Y
Y
Y
Y
Y
Y
Y
Runs 1 through 16 gave general comparison of semiweekly and triweekly
collections with and without transfer stations.
Runs 7A , B , C , D, and E tested sensitivity of responses to different random
number sequences.
Runs 17 and 18 were made to prove the model .
Runs 19 and 20 simulated triweekly collection in the Baltimore area under
investigation .
Runs 21, 22, 23 tested auxiliary compaction apparatus.
Runs 24 and 25 tested no queueing condition .
Runs 26 and 27 gave responses to two transfer stations in the area.
Runs 28 and 29 varied the tractor-trailer ratios at a transfer station .
Runs 31, 32, and 33 gave responses to three transfer stations in the area.
-------
-124-
1. PROVING THE MODEL
Two runs were made duplicating present Baltimore city system. The model
responses were compared with system values to evaluate the model . The
results are:
Dollars Tons Trucks
per ton per day needed
Model Run 1 10.67 295 29
Model Run 2 10.70 297 29
System 10.49 291 24-30
-------
-125-
2. MODEL RESPONSES TO INTERACTIONS OF VARYING COLLECTION
FREQUENCIES AND HAUL DISTANCES WITH AND WITHOUT A TRANS-
STATION
and
3. DETERMINATION OF CRITICAL DISTANCES BEYOND WHICH THE USE
OF A TRANSFER STATION IS ECONOMICALLY FEASIBLE
Sixteen runs were made for the above two objectives. Figure 6-2 incorporates
the results. Model policies for these runs paid overtime and assigned a suffi-
cient number of tractors that overtime averaged no more than four hours per
week per driver. The results were:
Run
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
Transfer
station
yes
no
yes
no
yes
no
yes
no
yes
no
yes
no
yes
no
yes
no
Collection
frequency
2/week
2/week
3/week
3/week
2/week
2/week
3/week
3/week
2/week
2/week
3/week
3/week
2/week
2/week
3/week
3/week
Haul
distance
24
24
24
24
8
8
8
8
16
16
16
16
4.
4
4
4
Total
cost/ton
$ 1 1 .08
14.41
11.97
15.08
10.57
10.57
11.38
11.56
10.65
12.53
11.49
13.32
10.30
9.48
11.15
10.31
-------
-126-
-------
-127-
4. MODEL RESPONSES TO INCREASING COLLECTION FREQUENCY
TO TRIWEEKLY
Two runs were made identical to those proving the model except with triweekly
collection rather than semiweekly. Haul was made by the collection trucks
to the incinerators as in the system. Comparison with the semiweekly runs
is made below:
Length of work day
Run Collection Max tons Cost Number
Number frequency per day $/ton trucks Average Stnd.dev,
17
18
19
20
2/week
2/week
3/week
3/week
295
297
338
341
10.67
10.70
11.62
11.65
29
29
36
36
6.8
6.6
6.4
6.4
1.5
1.3
1.5
1.6
-------
-128-
5. EFFECT OF AUXILIARY COMPACTING EQUIPMENT AT TRANSFER
STATION
Throughout most of this study, the assumption was made that the solid! waste
within the trailers was at a density between 400 and 450 pounds per cubic
yard. Auxiliary compacting equipment can be installed at the transfer station
which increases the pay load, having increased the solid waste density in
the haul trailers to the order of 800 pounds per cubic yard . Three runs were
made with the capital investment of the transfer station having been increased
by the cost of buying and installing this equipment, approximately $150,000,
and the trailer net weight limit having been increased from 30,000 pounds
to 60,000 pounds. Otherwise the new runs were identical in policies with
their counterparts without the compacting equipment. A comparison of
responses of semiweekly collections with and without this apparatus is
given below:
Number of
tractors $/ton $/ton
Run Compacting Haul and transfer collection $/ton
number equipment distance trailers station only total
21
13
22
9
23
1
yes
no
yes
no
yes
no
4
4
16
16
24
24
2 & 3
2 & 3
2 & 5
3 & 7
3 & 5
4 & 6
1.27
1.23
1.42
1.64
1.60
2.00
9.04
9.06
8.97
9.01
9.09
9.08
10.31
10.29
10.39
10.65
10.69
11.08
-------
-129-
6. SENSITIVITY OF COSTS TO NUMBER OF TRANSFER STATION!
UNLOADING DOCKS, A COMPARISON OF RESPONSES FROM
MODELS 3B AND 3C
Model 3B operates with unlimited unloading space for the collection trucks,
which results in no lost time in queues. Two runs, numbered 24 and 25,
were made using Model 3B . Other conditions were identical with runs
numbered 5 and 7, which were made using Model 3C, i .e ., two unloading
docks and queueing. The results of these runs are shown below:
Ave. time Total Ave. length
Collection % time at at disposal cost work day
Run frequency Model disposal (minutes) $/ton (hours)
5 2/week 3C 4.8 7.4 10.57 6.7
24 2/week 3B 3.8 5.8 10.57 6.6
7 3/week 3C 4.1 7.6 11.38 6.2
25 3/week 3B 3.3 6.1 11.34 6.2
-------
-130-
7. SENSITIVITY OF RESPONSES TO NUMBER OF TRANSFER STATIONS
IN THE AREA
Runs 1 through 16 investigated model responses with and without a transfer
station for different combinations of collection frequencies and haul dis-
tances. The urban area was further divided so as to be served by two
transfer stations, runs 26 and 27; and to be served by three transfer stations,
runs 31, 32 and 33. The results for a 12 mile haul distance are shown below
Figure 6-1 is a sketch of the area and the transfer station location when it
was served by a single station . Figure 6-3 is a sketch of the division of
the urban area and the two transfer station locations when served by two
stations. Figure 6-4 shows the same when served by three stations.
No. of
transfer
stations
None
One
Two
Three
Total no .
of trucks
31
24
23
24
No. of
tractors and
trailers
-
3 & 7
4 & 9
6 & 9
Cost of
transfer
stations
(dollars)
-
278,000
370,000
495,000
Cost
S/ton
12.10
10.61
10.75
1 1 .42
-------
-131-
AREA 2A
8 NEIGHBORHOOD
TRACTS
AREA 2B
5 TRACTS
A
T.S.
O
(T
-------
-132-
r
AREA 3C
4 TRACTS
AREA 3A
5 TRACTS
A
T.S.
T.S.
AREA 3B
4 TRACTS
A
T.S.
O
cr
-------
-133-
8. SENSITIVITY OF RESPONSES TO DIFFERENT TRACTOR-TRAILER
RATIOS AT THE TRANSFER STATION
An empirical equation is used in Model 3 which determines the number of
tractors to be assigned to a transfer station; this has been discussed in
Chapter 6. The use of the equation is optional with the user. Two runs,
numbered 28 and 29, were made with the number of tractors being one more
and one less than that given by the equation. Otherwise identical conditions
exist as in run 7, the run in which the model's equation calculated the
number of tractors. The results are:
Run
28
7
29
Value of
control
variable
NOTRC
2
0
4
No. of
tractors
2
3
4
No. of
trailers
required
10
7
6
Transfer
station
cost/ton
1.53
1.57
1.64
Ave . no . of
overtime hours
per tractor
11*
3
2
*violates arbitrary constraint of maximum of four overtime hours per week
-------
-134-
9. SENSITIVITY OF MODEL RESPONSES TO DIFFERENT RANDOM
NUMBER SEQUENCES
Five runs were made under identical conditions except for random number
generation . The control variable, K, was set equal to zero for all runs.
The model simulated triweekly collection with a transfer station, overtime
being paid, haul distance equal to eight miles, queueing occurring, and
no auxiliary compacting equipment at the transfer station . The model
responses included:
Run
7A
7B
7C
7D
7E
No. of
trucks
30
30
30
30
30
Tonnage
1537
1533
1539
1531
1546
$/ton
collection
9.81
9.76
9.84
9.81
9.72
$/ton
T.S.
1.57
1.57
1.56
1.55
1.56
$/ton
total
11.38
11.32
11.40
11.36
11.28
No. of
tractors
and
trailers
3 & 7
3 & 7
3 & 7
3 & 8
3 & 8
Hours of
overtime
for
trucks
32
35
36
34
24
-------
-135-
CHAPTER 7. CONCLUSIONS AND SUMMARY
Introduction
Three models were prepared in this study, the first two being somewhat
general in some of the assumptions upon which they are based, the last one
having the potential to operate realistically under most policies and
environmental variables of a real refuse collection system in an urban
residential area.
The general objective of this study was the preparation of such a model and
has been completed .
One of two specific objectives was securing order of magnitude of relative
costs of increasing collection frequency from semiweekly to triweekly.
This has been investigated for general conditions with Models 1 and 2;
furthermore it has been investigated for a specific urban area with Model 3,
Cost increases were found to be from 10% to 25%. The second specific
objective was the delineation of system properties under which the use of
a transfer station is economically feasible. This has been done for an
existing large urban tract with Model 3, and again, other existing urban
-------
-136-
areas could be similarly investigated with the Model . The feasibility
of the use of a transfer station is presented as a function of collection
frequency and haul distance between transfer station and final disposal
site for this urban mixed neighborhood tract.
The first specific objective, comparison of semiweekly collection costs
versus triweekly collection costs, is summarized in Figures 4-8 and 6-2,
and in Section 4 of Chapter 6. The second specific objective, presentation
of variable combinations for which a transfer station is economically
feasible in a collection system, is shown in Figure 6-2.
In addition to the above, other model results were obtained which are
indicat ive of probable systems responses to changes in policies and equip-
ment. Chapter 7 is now divided into separate discussions of the following
topics:
I . Limitations of Present Study and Areas for Further Investigation
2. Results from Model 3 Runs
3. Results from Models 1 and 2 Runs
4. Triweekly and Semiweekly Collection Systems
-------
-137-
1. LIMITATIONS OF PRESENT STUDY AND
AREAS FOR FURTHER INVESTIGATION
All models are structured so that performance data from another city can
be substituted for those used in this study. It is uncertain to what extent
the histograms and regressions used are representative of all urban areas
in the United States. A comparison of this performance information with
similar information from other large cities would be valuable. Severe
winter effects are not reflected in this study. Observations of weights of
solid waste produced and collection rates for triweekly collection would be
valuable replacements for the assumed values.
The large difference in the models' responses between neighborhood
type 1 conditions and the more dense areas suggests that neighborhood
type 1 is too large a classification . More meaningful results would per-
haps appear if it were less inclusive .
The data included weights collected, distances covered, elapsed times,
breakdown frequencies, and noted equipment types, costs, etc.; it did
not make population counts. Correlation between collected weights and
the number of people generating these weights was made from five years
-------
-138-
of records for the entire city, but information was not available for weights
and population generating them for smaller areas. Model 3 would be
improved if field data were gathered and processed so that the distributions
of refuse weights per capita per day by neighborhood types were available
for statistical testing for indications of significant difference . If the
distributions were found to be significantly different, the models' single
normal distribution of weight per person per day would be replaced by the
applicable sets for the four neighborhood types.
The location of the transfer station is fixed for the entire simulated week
of the operation. The location may be changed for subsequent runs, of
course. It appears that if a large area being served by triweekly collection
were divided into two subareas, with all collection trucks working in one
subarea on one of the week's routes, and in the other on the other route,
then economy could be realized if a mobile transfer station could serve
both areas on separate sites. The equipment would have to be of such a
nature that the daily moving from one subarea to the other could be done
easily and economically. This is similar to the situation of having two
transfer stations in the large area except the mobile concept presupposes
only one transfer station crew and only one investment in equipment. It
is thought that a completely new model would be needed to investigate
this system, although parts of Model 3 perhaps could be used .
-------
-139-
2. RESULTS FROM MODEL 3 RUMS
2A . Proving the Model
Many runs were made with the final model, Model 3; all had an existing
tract, the northwest quadrant of Baltimore or a portion of the quadrant,
as a working area . Most of the runs were made for the investigation of
operating policies which in time might be considered for the system.
However, two runs were made with policies and conditions as close as
could be obtained to the existing system, i .e ., no transfer station,
Baltimore pay scales and truck operating charges, no overtime pay,
semiweekly collection frequency, etc. Lack of similarity between
model and system included: (1) effect of adverse weather conditions
on operation; (2) the system fields a few small trucks in the area in
addition to the large trucks which are the usual type in use; the model
fielded only large trucks. The complete numerical results of the model
runs which can be compared with the system are in Chapter 6. The model
gave unit cost about 2% above the City's figure. Also the model indicated
approximately 2% more weight collected than the City indicated. The
model fielded 29 trucks daily to service the area; the City indicated from
24 to 30 trucks in regular use. These small discrepancies seemed to
-------
-140-
indicate a reasonably accurate model, the differences being easily attri-
butable to random number sequences and variations in the real system.
2B . Disposal Site and Transfer Station Site Planning
The costs of different proposed locations of disposal sites or transfer stations
can be estimated by making individual runs with each of the locations
incorporated in Model 3. The value of such comparisons may not necessarily
be merely the determination of which of several alternatives is the most
economical, but rather the securing of an estimate of the extra cost resulting
from the acceptance of a site which is not the most economical, but which
must be used because of other reasons, political, altruistic, etc .
2C . Critical Haul Distance for Transfer Station Feasibility
Figure 6-2 indicates costs for servicing the subject area with and without
a transfer station for triweekly and semiweekly collection frequencies.
Tt-e values are applicable only for the model's Baltimore data, but similar
curve, certainly with different val ues, can be obtained for other tracts
with other characteristics. The curves show a critical haul distance of
approximately eight miles above which a transfer station would be a good
addition to the system in northwest Baltimore. It is noted that critical
-------
-141-
distance is affected very little by collection frequency; it is approximately
the same both for semiweekly and triweekly collection frequency. A dis-
cussion of this follows:
The two lower drawings of Figure 6-2 illustrate that the two curves with
transfer station are parallel; the two curves without transfer station are
parallel also. In each case, the additional cost of increased frequency is
due to extra time in the collection activity and is not a function of the
traffic haul distance. The additional cost, the ordinate increment, is very
nearly the same between the two parallel sets. When the curves are over-
lain, the geometry of the resulting figure will be such that the critical
distance for a triweekly system will be the same as for the semiweekly.
If a transfer station is installed because of indicated efficiency while collec-
tion is semiweekly, it will be equally desirable if frequency is increased to
triweekly.
2D. Equipment Planning
Equipment decisions as to probable number of tractors and trailers, trailer
capacity, and the use or non-use of auxiliary compaction apparatus at the
-------
-142-
transfer station may be indicated by model response . This study's runs
indicated that the extra investment in the compaction apparatus is justi-
fied whatever the haul distance to the final disposal site. If the haul
distance between transfer station and disposal area were 24 miles, the
annual savings due to this auxiliary compaction apparatus would be of the
order of $31,000.00. This figure does not give consideration to maintenance
costs, if any, and possibilities of inconveniences of equipment breakdown.
However, for different traffic speed relations, different transfer station
capacities, different labor pay scales and tractor hourly charges, there
perhaps would be no similar justification for all haul distances, but rather
the responses would indicate a critical haul distance below which the equip-
ment investment would not be justified.
2E . Comparison of Complex Systems
A number of runs were made to determine the relative costs of several dis-
posal sites at different distances from the subject area. This may be expanded
for a situation in which a large urban tract has the choice of M disposal
sites and N transfer station sites. MN model runs will give responses for
the combinations of each disposal site with each transfer station site .
M more runs will give the same information for the simulated system oper-
ating without transfer station with delivery by the collection trucks directly
-------
-143-
to each of the disposal sites. More runs can investigate the possibilities
of the most economical arrangement being the joint use of more than one
of the transfer sites, each having a reduced capacity, combined with a
single disposal site. This latter thought was illustrated in this study when
the subject area was served by none, one, two, and three transfer stations
all with a final haul of twelve miles. This series of model runs indicated
that the minimum cost was realized with only one large station. As always,
the minimum cost situation can not be generalized as it depends on the
system being simulated .
With such usage for initial indications of costs and other system responses,
further investigation can be made to determine desirability of different
overtime pay policies, compacting apparatus, and type and capacities of
rolling stock.
2F . Effect of Queue ing
Model 3B operated with conditions of an unlimited number of unloading
docks while Model 3C had only two docks resulting in queueing at times.
The model policy placed an incoming collection truck in the shorter of
the queues if two queues existed and at dock number one if no queues were
present or if queue lengths were equal . System responses with and without
-------
-144-
queueing both for semiweekly and triweekly collection frequencies were
noted . The semiweekly cost for transfer station operation, which includes
the tractor trailer operations, increased $0.01 per ton with queueing; the
triweekly cost increased $0.02 per ton with queueing.
The average percent of time at disposal site for the collection trucks,
increased from average values of 3.5% to 4.5% with queues. Delays due
to queueing for the system being simulated cost of the order of magnitude
of 0.1% of the total system cost. The system responses are not sensitive to
the increase in unloading space, and thus it can be concluded that addi-
tional unloading docks are not justified.
2G . Number of Trucks and their Assignment to Areas
Tables 1 and 2 of the Model 3 print-out may be planning aids by themselves
without the remaining model responses being of particular interest. Table 1
divides each subarea into daily truck routes of equal number of household
units compatible with the neighborhood type of the subarea, the distance
between the subarea and the collection trucks' dumping site, and the col-
lection frequency. Table 2, using the information from Table 1, assigns
trucks which are numbered 1, 2, 3, etc ., to particular subarea routes by
days of the week. In this manner, an indication of the necessary number of
-------
-145-
collection trucks and their assignments for a proposed system is given to
the investigator. The control variable, ASSUNIK, is in the model for
this planning use. If the assignments for the trucks appear too large due
perhaps to some local constraint, reducing the value of this variable from
its normal value of 1 .0 to 0.9 or 0.8 will reduce the average assignment
somewhat accordingly, and vice versa.
Model results are improved if each subarea is sufficiently large that at
least three or four daily routes are within it.
The assignment logic programmed in the model places trucks about equally
over the entire area each day of the week rather than concentrating them
in different parts of the area on different days. This policy has two virtues:
(1) Trucks are not concentrated in a neighborhood on some particular
days of the week; and (2) The load of the incinerator or transfer station
is equalized between days of the week. To explain further, if on Mondays
and Thursdays all trucks are working with a long haul distance, and if on
Tuesdays and Fridays, all trucks are working with a short haul distance,
the Monday-Thursday assignment of household units will be appreciably
smaller than the Tuesday-Friday assignment. Different daily collection
weights will result from this. Further compounding of the weight differential
already resulting from different number of days since last collection is not
needed. This logic is not followed by all contemporary urban systems.
-------
-146-
3. RESULTS FROM MODELS 1 AND 2
The results from these two models served as basis for Model 3; this is
probably their greatest value. However, one of the specific purposes
of this study was the investigation of relative costs of triweekly versus
semiweekly collection, and results from these models gave insight into
this relation .
Figures 4-3 and 4-4 present number of households and gross acres covered
as functions of the affecting variables. This gross acreage is based on the
average ratios between net and gross acreages in the city of Baltimore
and certainly will vary with different cities. The plots showing the
number of household units serviced as functions of these variables are
of more general application. It is believed that these may serve a practi-
cal use in design as a starting point in task assignment planning.
The significances indicated by the statistical testing for "haul distance"
and "days since last collection" were anticipated. The significance of
the neighborhood type was also anticipated, but not to the degree attained
No significant differences in traffic velocities were indicated by the
statistical testing between the large and small trucks or between empty
-------
-147-
and full conditions. These results are contrary to beliefs held by some
supervisory personnel who are operating existing systems.
Runs with Model 2 indicated that the greater the assignment, the less
cost per ton of the simulated system. Two reasons exist for this. Firstly,
the crews receive a full day's pay regardless of the early hour at which
their work may be done during the latter part of the week. The increased
assignments eliminated these nonproductive manhours for which pay was
received. Secondly, Model 2 is programmed so that considerable off route
time is built into the regular work day, making the regular work hour
have only 45 to 50 minutes of productive time . The model, however,
treats an hour of overtime as fully productive except for truck breakdowns.
It is believed this parallels the system as long as overtime does not become
excessive. The model's responses to increased assignments suggest that
policy which causes overtime on the early days of the week and a full
day1 s work for the latter days of the week is efficient if acceptable to
the representatives of labor.
-------
-148-
4. SEMIWEEKLY AND TRIWEEKLY COLLECTION SYSTEMS
Semiweekly versus triweekly collection frequencies when simulated by
Model 2 indicate that little additional travel in traffic is required and
that the major additional expense when increasing collection frequency
is the additional mileage and time in the collection neighborhood. The
simulated triweekly collections, although more costly than semiweekiy,
averaged shorter workdays. The reason for this is developed in the
following discussion .
The difference in workday length between a first pass on a route and sub-
sequent collections in the week on the same route is greater for the tri-
weekly frequency than for the semiweekiy frequency. This compounds
the problem of task assignments; if they are made with the aim of a full
work day for the later workdays, the first of the week will be heavily
overtime. This study's models operate under the former policy of averaging
a full day's work the first part of the week and finishing early the latter
part, as it was believed this more closely duplicates most urban systems.
A semiweekiy policy generates three full days and three short days; a
triweekly policy generates two full days and four short days.
-------
-149-
The model' s results emphasized that a city making the decision between
triweekly and semiweekly collection must consider the relative weights
on the design capacity of the disposal points. Assuming that per capita
generation of waste does not vary with days of the week and assuming
equal number of households to be collected each day of the week, the
following table shows the percentage of week's total weight for each
day:
Percentage of Week1 s Weight
Collection
frequency
Fortnightly
Weekly
Semiweekly
Triweekly
Daily
Mon .
16.7
16.7
19.0
21.4
28.6
Tues.
16.7
16.7
19.0
21.4
14.3
Wed.
16.7
16.7
19.0
14.3
14.3
Thurs.
16.7
16.7
14.3
14.3
14.3
Fri.
16.7
16.7
14.3
14.3
14.3
Sat.
16.7
16.7
14.3
14.3
14.3
Less variance between daily total collections exists with semiweekly than
with triweekly policy. Theoretically this requires a larger transfer station
for triweekly than for semiweekly collection frequency. Figure 7-1
shows the above for theoretical percentages, which assume no extra
-------
-150-
/60>
% OF ,o
WEEKS
TOTAL
-
•
-
zz?
^
— -
1
THEORETICAL
PERCENTAGES
•••••
<•••
••^
•••
^» ^i^HI
M T W T F
DAYS OF WEEK
FIGURE 7-1
Waste Generation by Days of the Week, Baltimore System
-------
-151-
weekend waste generation, plotted against observed residential collec-
tion weights.
In addition to a reasonable safety factor in the design, this plotting suggests
that transfer station or incinerator capacity should be based on higher
capacity than that indicated by the theoretical daily percentages. This
increase is due to extra week-end waste generation (cross-hatched area
in Figure 7-1), imbalance in route assignments (difference in Figure 7-1
ordinates for M, T, and W), or a combination of the two.
If a transfer station is being considered, the decisions previously discussed
concerning workday lengths for collection trucks now become pertinent
for the station operation . If a triweekly frequency is system policy, the
number of laborers for transfer station operation on Mondays and Tuesdays
perhaps will be excessive for the remainder of the week. If a sufficient
number of tractors and trailers are present for Monday and Tuesday, drivers
and tractors will be idle a part of the time for the remaining four days.
Model 3 of this study has policies believed acceptable and probable in an
actual system. The transfer station staff of laborers was sufficient to handle
the heavy days and was constant through the week .
-------
-152-
The model makes no provision for overtime payment for transfer station
laborers as staggered shifts should eliminate the need for overtime for
these men . A driver was assigned to every tractor; overtime was planned
for tractors and drivers on the heavy early days of the week, but an over-
time constraint was imposed of no more than an average of four overtime
hours per week per driver. Actually it averaged appreciably less on the
model' s runs .
The model responses to triweekly and semiweekly collection frequencies
in Northwest Baltimore is seen best in Figure 6-2. The increase in cost
due to increased collection frequency remains nearly constant regardless
of collection truck haul distance or the presence or absence of a transfer
station. The indicated increase is of the order of $0.85 per ton, less,
than a 10% increase for the different conditions of the runs. The difficult
period of change in the system, the new route assignments and familiari-
zations, and the necessary planning of shifts for personnel probably prevent
change from semiweekly to triweekly policy as much as the increase in
costs.
-------
-153-
APPENDIX A
DATA FROM THE CITY OF BALTIMORE
The Bureau of Sanitation of the City of Baltimore operates residential
solid waste collection services daily except Sunday. Collections are
made twice a week from each residential unit within the city, either
on Monday and Thursday, or on Tuesday and Friday, or on Wednesday
and Saturday. The compacter trucks have a crew of a driver and three
laborers on Monday, Tuesday, and Wednesday; they have a driver and
only two laborers on Thursday, Friday, and Saturday. This arrangement
is because the first of the week collections contain four days' accumula-
tion, while the later collections contain only three days' accumulation .
The city has two sizes of trucks although many different manufacturers
are represented; these sizes are 13 cubic yard and 20 yard capacities.
The smaller truck is designated locally as a three ton truck, and the
larger is designated as a five ton truck. The smaller size is considered
less economical than the larger and so is used only in narrow alley
operations.
-------
-154-
Intensive data collection was carried out throughout Baltimore City in the
late winter of 1966-67. For a two week period every compacter truck
operating within the City maintained a log on the second complete trip
of each day. Baltimore normally has about 95 compacter trucks operating
daily. The two week period (twelve days) had a potential of 1140 reports;
approximately 4/5 were received in usable condition. Those not received
were due chiefly to trucks without speedometers and to a lesser degree to
driver illiteracy. The dumping times at the City's two incinerators were
observed and recorded by the author.
Discussions were held both with Regional Planning Council personnel and
with personnel from the City Planning Board of the City of Baltimore before
reaching a decision as to a simple manner of classifying urban residential
areas. The only considerations of interest were those which affected the
amount of solid waste generated per acre or the speed with which the
collection was carried out. The neighborhood classification finally
adopted was based on the number of housing units per acre of net residential
land. The term "net residential land" excludes public streets and alleys
and refers to the acreage in residential use only. The term "housing unit"
is defined [City of Baltimore, 1964] as, "a house, apartment, or other
group of rooms, or a single room occupied or intended for occupancy as
separate living quarters - i.e., the occupants do not live and eat with any
-------
-155-
other persons in the structure, and there is either (1) direct access from
the outside or through a common hall, or (2) cooking equipment for the
exclusive use of the occupants."
The study's classification of neighborhood types is:
Classification Housing Units per Net Acre
1 Ten or less
2 11 to 20
3 21 to 40
4 More than 40
The distributions of the number of housing units per net acre are not
generally uniform within the various neighborhood types in Baltimore.
Figures A-l, A-2, A-3, and A-4 show the actual distributions. These
histograms were drawn from in a random manner to determine the house-
hold density from which collection was made by each truck in each
model .
-------
-156-
sor
40
30
20
10
50
40
30
20
10
35 7 9 II
UNITS/ACRE
FIGURE A-l
NETYP=1
e 12 16 20
UNITS/ACRE
FIGURE A-2
NETYP=2
40
30
'o
20
10
-
20 3O 40
UNITS/ACRE
FIGURE A-3
NETYP=3
50
40
30
20
10
-
-
-
—
~h
40 60 BO
UNITS/ACRE
FIGURE A-4
NETYP=4
Distributions of Housing Units per Net Acre
by Neighborhood Type
-------
-157-
Weight Generated and Hauled
The daily weight of solid waste generated within Baltimore varies seasonally,
winter weights being as much as b per cent below the yearly average and
summer weights being well above the yearly average. Table A- 1 and
Figure A-5 give values and graphical representation of this variation for
the five year period including 1962 until 1966. The difference in weights
of solid waste to be collected from the same area on Mondays as compared
to Thursdays has been mentioned earlier. Figure A-6 shows values for a
three-week period in January, 1967. A seasonal shift in the weight of
solid waste generated was noted; it is due largely to yard clippings and
summer pruning and to a smaller degree to fresh fruit and vegetable
trimmings.
In Baltimore, drivers make the decisions as to when trucks have been
filled sufficiently to return to the incinerator for unloading. The field data
showed a very large variation in the weights and degrees of compaction
attained in returning trucks» It is noted again here that
none of these "full " loads were the last of the day. Figure A-/ shows the
distribution of "full" weights for 68 loads of 13 cubic yard capacity trucks.
Figure A-8 shows the distribution of "full" weights for 227 loads of 20 cubic
-------
-158-
2
0
t—
.
U
0)
Q
>
o
Z
•
o
o
-4—
Q_
^
"5
— >
O
CO
^t
| _
CO
_
.
o
ro
in
CO
o
,
co
^_
o
CN
CN
^~
CN
00
•
tx
CN
CO
•O
CN
0
-n
o
ro
•
ro
o
co
CN
o
co
in
in
CN
0
*
o
CN
3
CN
CN
CO
CO
CO
•^>
OO
CN
-0
X
CN
rx
IX
CM
CN
00
CN
O
o
CO
tx
rx
CN
O
o
co
^o
o
ro
CM
tx
CN
CN
00
CN
33
CO
CN
CN
"3-
CN
O
^O
CN
t/t
_c
•4_
c c
— 0
•0 5
0)
±; x
0 _Q
s s
i) i_
o <
c "o
— 1— **
i o V:
< 1— C
- 8-S
i K^J ,_
°=> ° £
•< _*" C£
1— «,
c -1"
— X
-*-
0
- .§
c5 —
1/1 &
-------
110%
K 100 %
90%
-159-
•o UL 2 < 2 -3 -> < cnOzo
K =
Production in Indicated Month
Average of All Months' Production
FIGURE A - 5
Monthly Variation of Solid Waste Production, Baltimore City
Five Year Average, 1962 - 1966
-------
-160-
O
o
ro
o
o
CM
o
o
o
o
o
o
o
O)
0
> Ul
< I-
Q O
o
o
oo
O
o
o
o
IdJ <
Q3M
301
NOW
IVS
O
nni
Q3/V\
3fll
NOW
o
o
10
vO
I
o
01
PQ
0)
4-1
(O
O
t/1
m
ID
•r-l
U)
01
O
CO
oo
•r-l
-------
-161-
40%
20%
Small Trucks
r-T
O
o
O
IO
o
o
o
o
o
o
o
m
NET WEIGHT IN POUNDS
40%
20%
Large Trucks
o
o
o
in
O
O
o
o
o
o
o
in
NET WEIGHT IN POUNDS
FIGURES A - 7 & A - 8
Distributions of Trucks' Full Weights
-------
-162-
yard s capacity trucks. The larger capacity trucks achieved only 79 per-
cent of the compaction which was obtained by the smaller capacity trucks;
the former having averaged compaction of 435 pounds per cubic yard and
the latter 550 pounds per cubic yard . The daily weight of refuse per capita
in Baltimore averages 1 .95 pounds with a standard deviation of 0.09
pounds. These values were used throughout this study.
-------
-163-
TRAFFIC
Distances and trip times were noted for 456 trips of collection trucks on
Baltimore streets. These trips were equally divided between empty from
the incinerator and full from the collection areas. Figure A-9 shows the
distribution of these traffic speeds. Figure A-10 and A-11 show the same
data, but have presented them in two histograms, one for empty conditions
and one for full conditions.
A common claim for the smaller capacity trucks is that a reduction in
haul time is realized with their use because of traffic maneuverability.
An analysis of variance two way test was made on four cells of thirty
data bits each to determine if significances were indicated of the effects
of trucks capacity and loaded or empty condition, or interaction of the
two, on traffic speeds. The four cells were:
a. 13 cubic yard capacity empty
b. 13 cubic yard capacity full
c. 20 cubic yard capacity empty
d. 20 cubic yard capacity full
The analysis of variance results are given in Table A-2; no significant
differences were indicated in traffic speeds whether tull or empty, or
-------
-164-
V)
o
DL
u_
0
fO
O
(VJ
CM
»O
(M
X r-l
00
o
C)
o
3
(£
(VJ
CM
10
00
W
C!
O
JQ
•i-l
M
-U
0)
-rJ
O
0)
o.
CO
o
•r-l
14-1
0
10
0
OJ
OJ
ro
1
l_
0 0
•0 CM
1
1
O
CM
X
Q.
CO
g
-------
-165-
Source of Variance
ANALYSIS OF VARIANCE TABLE
Sum of Degrees of Mean F
Squares Freedom Squares Ratio
Between empty and
full condition 0.533
Between 13 yard and
20 yard sizes 2.700
Interaction 0.299
Residual 2931 .27
116
2.700
0.299
25.27
0.02
0.08
0.01
TOTAL
29J4.8
119
F (1,116) at 0.05 =3.92
TABLE A-2
Test for Significance of Truck Size and Loaded Condition
on Traffic Speed
-------
-166-
whether 13 or 20 cubic yard capacity.
Figure A-12 shows speed versus trip distance for 99 of the above 456
trips. The 99 were chosen randomly. It is noted that speeds are dis-
tributed heteroscedastically. Figure A-13 is a plot of logs of speeds
versus distance for the same data and the ordinates, the log of speeds,
are homoscedastic . The least-squares regression equation of log speed
on distance is:
Log Speed (mph) = 0.978 + (0.0419 * Distance in Miles)
The standard error of estimate is 0.1366
The index of correlation is 0.407
Figure A-13 shows this regression equation on an arithmetic
ordinate scale .
It may be noted in Figures A-12 and A-13 that data extend only to a
traffic distance of about fifteen miles. Beyond this value, it was assumed
that logs of traffic speeds would vary normally around the upper value
of log speed given by the equation for the fifteen mile distance .
-------
-167-
o
0)
o
c
tfl
g
4)
0)
CX
o
•H
M
H
O
•r-l
CO
CO
4)
H
00
-------
-168-
\ \ : \
CO
UJ
UJ
o
Q
O
-------
-169-
COLLECTION
Baltimore is divided into tour different areas, termed divisions, by its
Bureau of Sanitation. The neighborhood types range from open high
income areas, through middle income single family and apartment units,
to very congested high density slums. The collection rate in pounds per
hour appears to be low in the sparsely populated areas, becoming high
as housing density increases and then seems to vary in extremely high
housing density areas because of the crews' lack of work area for their
activity. Logic also suggests that differences would exist in collection
rates dependent on the number of laborers and the number of days since
the last collection.
A great amount of data was collected to clarify the above points. During
the period in which the field crews were keeping logs, 315 periods of
collection were noted for total weight collected, time spent collecting,
number of laborers on each truck, neighborhood type, and days since last
collection. Decisions were then made of the type and number of distributions
from which to draw in the models for realistic portrayal of collection
activity.
-------
-170-
Th e data from neighborhoods of housing densities greater than ten units
per acre were first subjected to an analysis of variance two-way test to
check the indicated significance of dense neighborhood types and collection
frequency on collection rate. The test was conducted with 12U values of
collection rates in units of pounds per hour. The values were taken
randomly from the entire field data.
The analysis of variance results are given in Table A-3; the results show
no significant difference indicated in collection rates because of difference
in neighborhood types or days since last collection.
A second two-way analysis of variance test then was made using the same
data plus two more cells with 20 data bits in each from neighborhood type 1
for both three and four days since last collection. These results are given
in Table A-4 and show very significant difference indicated in collection
rates because of the different situation of three days since last collection
against four days since last collection.
Also this second test indicated significant differences m collection rates
between that for neighborhood type 1 and those for neighborhood types
2, 3, and 4.
-------
-171-
ANALYSIS OF VARIANCE TABLE
Source of Variance
Between collection
frequencies
Between neighborhood
types
Interaction
Residual
TOTAL
Sum of
Squares
460.2
177.9
942.9
16,418.7
17,999.8
Degrees of
Freedom
1
2
2
114
119
Mean
Squares
460.2
88.9
471 .5
144.0
F
Ratio
3.20
0.6
3.28
F (1, 114) at O.Ob - 3.92
F (2,114) at 0.05 = 3.07
TABLE A-3
Test tor Signiticance of Neighborhood Type and Collection
Frequency on Collection Rates
for
Neighborhoods of Greater Than 10 Housing Units per Acre
-------
-172-
ANALYSIS OF VARIANCE TABLE
Sum of Degrees of
Source of Variation Squares Freedom
Between collection
frequencies 1,722.7 1
Between neighborhood
types 3,355.5 3
Interaction 1,/«3.0 3
Residual 32,593.7 152
TOTAL 39,454.9 159
Mean F
Squares Ratio
1,722.7 8.05
1,118.5 5.24
594.3 2.7«
214.4
F (1,152) at O.U5 - J.VO
F (J,152) at 0.05 ^2.64
TABLE A-4
Test for Significance of Neighborhood Type and Collection Frequency
on Collection Rates
for
All Four Neighborhood Types
-------
-173-
On the basis of this information, field data were incorporated into three
histograms showing distributions rates for particular field conditions.
Figure A-14 shows the observed distribution of collection rates within
neighborhood type 1 with three days having elapsed since last collection .
Figure A-15 shows the observed distribution of collection rates within
neighborhood type 1 with four days since last collection .
Figure A-16 shows the observed distribution of collection rates within
neighborhood types 2, 3, and 4. This histogram is applicable with
crews with either two or three laborers and with eit her three or four days
since last collection . Table A-3 showed no significant difference indi-
cated in collection rates due to these sources of variance .
Figure A-17 shows the assumed distribution of collection rates within
neighborhood type 1 with a crew of a driver and two laborers and with
two days having elapsed since last collection . Figure A-18 shows the
assumed distribution of collection rates within neighborhood type 2,
3, and 4 for the same conditions. The assumed distributions are
used in the simulations for three times a week collection . The assumed
-------
-174-
40
30
OF CREWS
20
10
5000 10,000
POUNDS PER HOUR
15,000
FIGURE A - 14
Observed Collection Rates, Neighborhood Type 1,
Three Days Since Last Collection
OF CREWS
100 15,000
OUR
FIGURE A - 15
Observed Collection Rates, Neighborhood Type 1,
Four Days Since Last Collection
-------
-175-
30
20
OF CREWS
10
<
VE
3T
161
HE
HBORHOOD TYPES
R THAN 1
rn
0 5000 10,000 15,000
POUNDS PER HOUR
FIGURE A - 16
Observed Collection Rate, 3 & 4 Days Since Last Collection
40
OF CREWS
20
10
NEIGHBORHOOD TYPE *
fl
0 5000 10,000 15,000
POUNDS PER HOUR
FIGURE A - 17
Assurred Collection Rate, 2 Days Since Last Collection
-------
-176-
30 r
2O
OF CREWS
IO
50OO 10,000 15,000
POUNDS PER HOUR
FIGURE A - 18
Assumed Collection Rate, Neighborhood Types Other Than 1,
Two Days Since Last Collection
-------
-177-
distributions are similar in shape to the observed ones from the same
neighborhood type and with the same number of laborers, but are shifted
1000 pounds per hour to the left because of the assumption of having
only two days since the last collection rather than three. This condition
would reduce the collection rate. No observed data were available either
from Baltimore or from other cities for this condition.
The Baltimore tield information included average speed in miles per hour
of the trucks as they moved through the collection streets and alleys.
These speeds were calculated by dividing the mileage covered by the
truck while collecting by the elapsed time spent collection (Table A-5) .
Table A-6 was not used in the models, but the information within it came
from that from which the histograms of Figures A-17 and A-ly were prepared.
These latter assumed collection rates for untested conditions. These data
indicate the lessened production per man per hour of the three-man crew
compared to the two-man crew for the densely populated areas. However,
when three-man crew is used, Monday, Tuesday, and Wednesday, the work
day in Baltimore averages about 40 minutes longer than that of the last
three days of the week.
-------
-178-
v»
2 °" ~o
£z£
o.
5
c
I/I
•o
a>
d>
Q.
CO
O 10
• o
o ••- o
-0 0
• o •
"t *- iO
0 -0
• 0 •
••* *- t
10 o °.
ro *" *t
° o "1
ro ^~ c*j
^ 0°.
CN *" CO
C\) *• CN
•o o
• O •
— *• CN
0 o 10
* *- •
' "
« o°.
o *• —
iO
o P -
•*• o
"8
0
_c
1- VI
O
E
3
Z §
u_ ±_
O 0)
o £
\J
iO '-^ T>
1 3 (U
< .€ g.
LU *: co
— ' —I-,
3 o ^
<< *-
i— CD o
c c
•- en
| s
Co Q
(/>
T)
(U
8.
CO
o
O
0)
"o
U
-------
-179-
5
d)
i_
U
1_
0)
_C
QJ
0
^
X
^f
JO
_l
O 0 O 0
o-* o— oro *o
•"d- •— rofo OCM -oco
- U -II V II V II
IOC -OC -OC IOC
c
o
5
\
k_
I
\
<«
n
i
O 0 0 0
^O^t O— COCO X>O
»•— •— n OCM x>co
v ii ^n v || ,.11
r— C CMC CMC r— C
2
u
£
I
l_
U
x.
c-
x
•>
-Q
__l
o o o o ro
no CMO Or— oo
.— CM tCM CMCM — r-
^11 V II -II -II
coc ir>c r>c -oc
C.
O
-5
•<
X
^
•X.
t/>
ja
i
LO o
0)
0
t^.
g
-+—
U
"o
(J
2L
O
JD
-------
-180-
DUMPING
The City of Baltimore has two incinerators, the newer termed the Pulaski
Incinerator and the older the Reedbird Incinerator. The Pulaski has a
rated capacity of yOO tons per day and the Reedbird 600 tons per day.
The Pulaski has nine unloading docks and the Reedbird eight. All loads
are weighed, and both incinerators accept commercial trucks fora tee.
Several half-days were spent observing the dumping activities. It was
noted that queuing at the unloading docks seldom occurred unless there
was a truck breakdown or difficulty with the scales. The commercial
trucks without dumping or ejecting mechanisms often required a very long
time (15 or 25 minutes) for unloading into the pits. The automatic ejector
city trucks actually unloaded, not including moving and weighing, in
about three minutes as compared to five minutes for the city dump-type
trucks.
The histogram shown in Figure A-19 shows time intervals between truck
arrivals at the incinerators. This represents data from 1M arrivals at
Pulaski and 11 7 arrivals at Reedbird . These times of observation were
-------
40
30
20
10
FIGURE A - 19
-181-
345
MINUTES
Time Interval between Truck Arrivals at Incinerators
-------
-182-
for "average to busy" conditions as estimated by the scale operators.
The times were generally 9:30 to 11:30 AM and 1:00 to 2:00 PM . Figure
A-20 shows "service time" for city trucks only at the two sites for 50
trucks at each site . "Service time" is elapsed time between the truck
entering and leaving the incinerator yard. Field observations indicated
approximately 16 percent of the trucks were commercial, and city records
indicate that 14 percent of the tonnage handled is from commercial
trucks. Table A-7 gives the data from incinerators from which Figure
A-20 was prepared .
Figure A-20 is bimodal, as are the data for service times from both
incinerators. This is due neither to sizes nor types of trucks, but
rather due to some of the crews leaving their trucks while dumping to
use the facilities at the site . When this "off-route" time was not used,
the city trucks dumping times were massed around the left node .
-------
-183-
30 r
20 -
10 -
r- 3O
PULASK INCINERATOR
-
.
r—
2O
Yo
IO
-
^
REEDBIR
INCINERA1
1
02 4 6 8 10 12
MINUTES
0 2 4 6 8 10 12
MINUTES
30
20
10
ABOVE
COMBINED
02 4 6 8 10 12
MINUTES
FIGURE A - 20
Incinerator Service Times
-------
-184-
Service Time
Interval
In Minutes
0-1
1-2
2-6
J-4
4-5
5-6
6-7
7-«
B-9
9-10
10-1 1
Pulaski
Site
0
4
4
11
8
4
3
3
»
4
1
Reed bird
Site
0
4
6
15
12
4
1
1
4
2
1
Total
0
8
10
26
20
b
4
4
12
6
2
5U
100
TABLE A-/
Service Times at Baltimore Incinerators
-------
-185-
APPENDIX B
DATA OTHER THAN BALTIMORE FIELD OBSERVATIONS
1 . Transfer Stations
Information of the physical arrangements, the costs of operations,
and operating policies of existing transfer stations were gathered
so that the simulation model transfer station could hopefully
duplicate existing successful ones.
Transfer station information was received from Chicago, Denver,
New Orleans, Beverly Hills, Santa Monica, Reno, and Abilene,
Texas. Particular values are given in Table B-l .
The New Orleans stations is unique in that overloaded or shut-down
incinerators are used as transfer stations. The collection trucks
dump directly into the incinerator pits; the incinerator crane then
loads into a chute and on into trailers.
The trailers cost from $17,000 to $20,000, and the tractors between
$11,500 and $li>, 000. The cities, excepting Abilene, Texas repot ted
-------
-186-
D
flj
CD
y
>
o
^
i
d>
6
#
£
^
,_,_
N
L/^
"o
Q
Z
"^
£~
X
14_
0
d
X
u
§-
o
_Q
E
Z
X
^o
0
^1
2
CO
^
V)
C
Z
c
£
™~"
o
I
ti
~
U
8
C
o
•#••
5
O)
c
8
•5
*
0
~5
o
I
0
c
o
o
O CM
CM —
CO CM
03 O
^" ^
i~~
*
O O
o o
— o
"~
0 0
o o
o o
o" o"
CM •*
— CM
if) O
— CM
.
~o
o
°5 ^
o S:
.S* c
f
CO C
-------
-187-
little or no compaction within the trailers. Split level loading was
done at all stations with the collection trucks either dumping directly
into the trailer, directly into a chute, or onto a concrete ramp trom
where a bulldozer pushed the solid waste into a loading chute.
The cities of Reno and Beverly Hills were outspoken in the beliet
that their transfer stations were efficient and successful parts of their
solid waste collection systems. Beverly Hills gave an operating cost
on each tractor-trailer combination of $1 .16 per mile, which includes
depreciation.
2. Cost Information ot Existing Collecting System
A number of cities answered questionaires relative to costs and
policies of their collection systems. Table B-2 gives values. Comments
on the replies tallow;
Boston's collection is let by contract and the values shown tor it
are supplied by and applicable to a private firm.
Most of the cities which show no overtime pay give offtime, hour
for hour, tor crews overtime period. A number of cities for which
the table shows overtime pay at the rate ot time and a half give
-------
-188-
<0
O)
o
c
0
<1>
Q.
73
C
O
~o>
D
u_
TO
- O
• 5
<-» 0
I/I
u
D
£
U)
_*
O
3
i_
*0
o
> a:
X
~z o-
3^
X
ir -*-
0 eg
X
X
1 «
x5
X
u
o
o
CO
-o
0
CN
1
1
0
z
iO
o
CN
3
CN
Atlanta
»
i
00
o
CN
to
O
CN
1
1
O
Z
-o
•—
o
tx
CN
O
£1
TO
C
|
CO
lO O O O
CN — 1
O
1 1 1 CN
1 1 1 CN
lO O X> -O
to o o ^i-
CN CN CN —
CN CM CN
.— _ ( r—
?— — | —
v> v> -. w»
fl) fl) f ' fll
> > z >
co r^ x> t
•— lO CM fX
CO CO CN —
X> lO O "O
r- (V, rf O
CO CO CN CM
-o
o
5 si s
*/> *TT Q} ™
:2 U D Q
^0
•o-
1 O
1 ^0
0 X>
0 0
CN —
CN CN
p^~
, — —
- >
CN O
•*t x
CN CN
CO O
o o
CO CN
Denver
Detroit
i
10
0
•—
X)
PO
o
•—
1
1
o
z
x>
o^
•—
o
CN
Houston
o
i
i
x
o
CM
1
1
O
Z
1^
CO
—
o
—
c
o
L_
O
0)
z
in
CM XI CO
i
CN
O — 1
ro »— i
O lO X)
0 X) X
CN — —
rsi
\
i |
i i ~~*
o o S
Z Z >
CN CN »
<4- X> X
CN CN ro
X) CO X>
CN CN CO
a
'i-c
-ir en
-S 3 »
D 5 i:
— t: o
j: ~
1 —
^
CN
8.
E
o
CM
X
c
o
~o
X
UJ
'o
o
o
Q
-------
-189-
double time pay for work exceeding ten hours in a single day.
Most cities showed a range of hourly wages reflecting longevity increases,
The values shown in the table are maximum for the job.
-------
-190-
Appendix C
DATA GATHERING FORMS
TPiAFFIC SPEED DATA SHEET
To be completed by driver
Trip with truck empty
On leaving incinerator
or disposal area
un arriving at
collection area
speedometer
Mileage Reading is
Clock time is
Weather is rT clear Q rain nsnow
Trip with truck full
On leaving collection
area
un arriving a\; incinerator
or collection area
iapeeuome'cer
Mileage Reading is
Clock time is
Weather is /"/clear /_"/ rain fj snow
To be completed by supervisor
3. City ^
k. Date
5. Driver or truck identification
6. Truck type & capacity
7. Were these two trips on
rj Mainly city streets or residential streets
'J Mainly thoroughfares & highways
;~t About half & half
8. Comments
Signature of Supervisor
Solid Waste Collection Study
The Johns Hopkins University
Department of Environmental Engineering
513 Ames Hall, Baltimore, Md.
-------
-191-
CITY OF BALTIMORE
COLLECTION SPEED DATA SHEET
To be completed by driver while in Collection Area
1.
When emptying first can
for this load
When einptying last can
can for this load
ClocK time is
Speedometer
Mileage
Reading is
2. Weather is o clear (Train 0 snow
3. Collection is chiefly from IT) front curb cans /i» alley cans
h. Days since last collection [U 1 Q2 Q3 fl1* or (~:i
5- Crew size is the driver and Q1 D2 f';3 p ^ men
6. Weight of this load is pounds
To be completed by supervisor
7. Division D NW DKE OWest MEast
8. BSrough No.
9. Task area of collection
10. Date
11. Driver or truck identification
12. Truck type or capacity
13. Comments
Signature of Supervisor
Solid Waste Collection Study
The Johns Hopkins University
Department of Environmental Engineering
513 Ames Hall, Baltimore, Md.
-------
-192-
Appendix D
COST CALCULATIONS FOR SEMIWEEKLY AND
TRIWEEKLY COLLECTION, CHAPTER 4
O
H
§
H
H
f-i
Q
I
- r-i CM ts| cr> ^0
O 1-1 CM n -j- in
/-4 -^ r-< CSJ
1— 1
f^
I— I
\& ao ts) iTi o\ o\
t~~ r^- o O vo ro
r^. in oo in ,-1 oo
CTi O\ CTV CT\ 00
CM CM O P- 00 OO
»— i i— i r— i— > r^ r-4
r-i o oo OO r~ r~ \D O CM 00
r-4 m LO O e— 1 IT>
vO
r^- vo m r^. ^ /— i r^ in
t — vo vO -d" vO
^O ro r-l O ON 00
r-t i—> i-t r-l
l/N, ON ON CM f—
-------
-193-
§
H
§
H
M
a
r-l 00 f» SO
O C^ O> OO QO OO
r-l O CM O CM ^f
r- O m CT> -d" CO
vD vO m u~> '« r-i oo cr«
rO \O vO CO OS
»-l <± CO CM OO t~- ^ vO vO
CTs 00 00 OO OO 00
r-i r-( in vo cr>
vo r^ r«- I-H ro n
•— i co r~. r~ \o in
r*
n ^o
CM oo \o ~j- o vo
o oo r-- i*« vo m
F-I
CM ^O ^ vO ^>
CO O »J 00 CO CM
cn
m
CM
» r^
00 oo QO oo oo oo
i— i i— i vo <^> m ' —
CTi ON in CM CM u~i
o oo i-- r» vo m
i-l
f» O r-l l~~ i-l O vO
00 CJ\ i-4 CM -J m
r-l CM
-------
-194-
0
H
§
H
"^
in-
H
CO
Q
M
g
oo ON CM r~ o> O
in oo oo r-» oo oo
OO <"O *— ' *— 4 O^
CM O ON CT* 00 vO
f— 1 r-l
ssssss
O i-l CO CM xt" vO
f-l CM m CM VO CM CT>
M 2 r^ ^ ^ "^
co P* in »-i i-i cr>
*™^ C7* CM CO vO CO
r~» oo O O r-l co
r-i CNI
CM O <}• ro ^H OO OO
j r^» vo CM ^d" vj*
^0 xf ^o *kO o^ ^o
in co i— i o cj\ oo
o co *— * in ^o oo
CO O1^ C^ >^ C7N oo o O •-« CM
r-l -d" CO CM OO
-------
-195-
to
2;
O
§
H
H
co
w
o o vt CM en O CM CM i->
O CT\ O Os ON CT>
«-l 1-1
r-t vo <-i i-4
O\ CO f-~ vo >i> Ti
vO r~ o O 00 co
r-» o PO 10 o> oo
O CM 00 cr\ cr> o
o\ r^ oo co oo o
«N cr> oo oo vo o
i-t
co oo r» ~3- IT)
\O oo o\ (T>
r~- r-» \o vo u"> r*>
00 OO 00 OO 00 CO
CM CM O\ «^> 01 O
•-i co vt LO ON m
CM OS OO CO ^O vf>
r- <
m o> <}• o oo r^-
CM 00 i-l r-l fO 00
r- fo o O CM <*^
•-I O
u~l O r~ CT> oo u-i •<}•
t*» OO CTV O 1-1 rO
•-I J-
•-I ^-1 CM
-------
-196-
13
o
S3
23
§3
co O
Q
rx,
O CO
z
§o
EH
C/N
u
o
•J 53
S 3
-t; H
ffi CO
M
Q
CO
g
OS
3C
0
.^r"
t-M
Pn
Q
0
O
§
O W
m K
Si >>
0 H
W
z
co I-H ON ON vO r-.
m o r^ o >* oo
O CM en en -4- vo
rH rH rH i— 1 r-l i-H
CO ON VQ rH CM ON
ON in O rH CO O
|x> ON O ON vO <±
C>"> rH CM O O O
i~~ r^ o
^O CM CO O CM i-H
CM OO >X> m O O ON CO
vo 00 O O rH fl
rH rH rH rH
CM fl CT< f>« f*» O>
CM r-4 in O r^ t*J f*1
rH O O O ON CT\
CM CM CM CM rH rH
O ON rH OO C*1 tn
-3- r«- in m rH cTi
o CM o o \o ro
ro c^4 CNI c^l i>~4 r^
rH .O O
P~ IX. r~. rH rH CO
O TO ro rx, in i/i
O O O ON O ON
CM CM CM r-l CM rH
rH ON -J- in CO ^J"
CM
-------
-197-
o
s
(X4 C/5
O 03
en O
Q
O en
z:
w
11
h-(
Q
en
•z
&.
Drf
i
a
NEIGHBOR
TYPE
in - o
CM >d~ .o CM in
CM CM CM CM CM in in
CM CM r-l —1 r-l r-*
r-l -<)- co co in r-i
oo r^> r*** vo ^o vo
CM CM CM CM CM CM
o
co m CM co co co
o o f^ in CM oo
JD O m CT* CO CM C7^
CO C^ vQ in r-l ty\
CO CO CM CM CM r-l
r-l
-------
-198-
CO
>> CO
fM O OO ft i-l
ON OO 1^ vO vO in
vO r^ o O oo co
r^* CO co in ON 00
O CM t~l r~»
1
m CM r-l r-l O. CM
ON OO O
-------
-199-
1
§
CO
Q
H
a
CO JS
3
CO 2
H
ASSIGNED DISTANCE I
TASK OF HAUL
CO i— 1 O*N ON vO r*^
m O r- o — I
O CO CO ON O OO
O O ON ON O 00
CM CM r-l r-l CM r-l
O ON in ON O CN|
r- r-~ o oo o oo
,O r*** vO if} ^O ^^
00 00 00 00 oo oo
\O CD i— ^ f^ c~i *^J"
r* in i— i co co co
r-i oo -cf in co
vO OO ON f^^- CM vO
vO in * so in in co CM
in r^- in r-~ -^ ON
O CO CM sO vO OO
ON in •— i O oo m
rH CM SO O CO CM
»j- oo o ON o oo
CM O ON 00 OO sO
1— 1 l—t
-------
-200-
<: o
Q o
CO
§
H
§
H
CO
- H
>• CO
-t: o
Q O
§
H
UJ
CO
r-l
O O
t-l
co H
CO
<<
oo o** o> o
CT\ r* oo oo oo o
CM O\ OO OO ^O vO
oo <± ^r oo oo ,
* O CO
oo r-i ^J CM r-- oO
^H r1^ ^^ r~^ \jQ r™**
J> (^ CT* O^ OO OO
iO tO VO **O vO vO
%O «-l CM O OO 00
vO O
^t 00 r-l r-l O CO
t
to O O O ON r^
CM vO (^> i— 1 lA
OO r^ ^o fO co
u-i ON oo o oo to
r- ON O ON ro
-------
-201-
§
H
GO
Q
c/5
Q
o
H
to
Q
rO
H 32
OO
r-4 fr,
Q O
o
en H
c/3
CO vO ^ 00 OO 00
ON CJN O O ON OO
vD OO O O r-4 ro
r-4 (—4 r-4 i—(
CM ro ON r- i~» ON
C>J r-4 m
O CM O O \O ro
r-- IA oo ON o> o
o\ r~- oo oo oo o
CNl ON OO OO \O \O
ro
!»• CO i-» i- 1 ON I""-
r-4 oo ro m ts ON i-t fM
1-4 i-l
rt m o f*> CM <-*
OO — 1 rH •— 1 \D 1 —
ON ON CT> ON OO OO
r-» m o> ON cvi ro
CT> ro vO P~ vO O
•-i' f^ O
t>» ON >— 1 <— ' <""! vO
»-l ^-1 r-< r-l
1^* r-* -J- ON i— 1 i— 1
OO CM i-l CM \O 1^
ON CM oo r~ ON oo
ON O> ON ON OO OO
ON f- CO ON OO O
CNI ON ~~ f!
^o t~- CM r-i jo r-i co m ^o
m CM CM CM oo xt-
^O CO ON ON ON <— 4
r-4
00 in IO vO r>- OO
O CO OO CM CM CO
0)
2
-------
-202-
tn
- H
>-i CO
< O
O CJ
O
H
O
H
cd
flj
CO
- H
>< CO
< O
O
O
H
O
W
c/l
I— I
Q O
G
w
to H
en
CO O ON vO ON 00
\& co O -3" P""" co
oo oo oo oo oo oo
ON| Csl ON vD CO CD
*—i oo ^3" *^ ON ro
CNJ ON 00 00 >sO vO
co ON -d' O oQ r-^-
CSf 00 *-* r-* CO GO
r*- oo O O CM co
t~4 r-4 rH ,— )
S
rO cO r^ r-* oo OTN
rH rH <)- OO 00 in
r- cyi cr> CT> O CM
rH rH
m
rH
r-~ O O m CT> rH
OO 00 00 00 OO OO
JN in o^ ~-^ ox ox
ro co CM r-l oo CM
^ oo P*» ^~ m in
rH
in OX O rH CM rH
CM rH 00 OO o
rH rH
rH *£> OX CM O CM
ox r^- rH CM r^* o
t-- Ox rH rH rO in
rH rH rH rH
m
m
rH <)• 00 rsl (X) . oj ON r^. GO
LO r~^ oo r~*» cr\ ON
r-
CM rH OO 00 CM *«o ro in
rO OO rH O ^ rH
r^ O in co rH CM
CO OX vX) vO CO CM
CM rH rH rH rH rH
m O CM i— 1 ro vO
•"O Ox r^ <)• CM -3"
r^ OO Ox O O CM
rH r-l rH
m
rH -,t OO CM OO
-------
-203-
z
o
H
co -
Q
co
CO
Q
CO
Z
O
H
co O
Q H
co O
Q H
W
U rJ
Z S
la
C/)
M fn
Q O
O co
M <£
CO H
CO
co en CM CM — I i— I r-l m
CD .-i O O 0\ en
CM CM CM Cxi r-l r-l
CO O CT> vO en OO
vo to o i— 1 r~ r-» CTi
t^ CM in CT> vO vO ro O
r-l OO oo oo >o vo
i— i
O u~i O <}• O> rg
CM O OO
r-l vO <^> *-O
ON r— c*l vo ro <)•
>i) 00 O O r-4 CM
/-I r-l
u"l CTi CT> lA r-~ O
m m CM m CM <-i
r^ oo oo
ON CM cr\ oo m r~»
r-l VO CM CM 00 kO
oo r<» CM \o o O
O r-i oo r- ov CM
CT* CTA CT» CTv
1— 4 r-l c-4 i— 4 iH r-4
CM O\ CM O CO v£>
r^ o o in o> <— 4
u~> m >-D in oo ON o d O
O 00 vo r^ 'A ^O
r^ O O O O O
v£> o m oo oo m
ro in oo r-» in ro
^D ^D CO CNJ
cr\ in GN
i—4
1 in vO -J- (T> MD
cr» r-4 in in O~> f^ 1 —
r-4 cr> o r- 1
rH r-4
O CO ^O CM CM in
CO ON ro O i^-
co O CM r-- i— i CM
r^ oo >£> vO co j — 1 O CJN CT» CT>
r-4 r-4
CM r-l OO OO CM CM OO
-------
-204-
Appendix E
RESULTS FROM MODEL 3
°co
K i^J
M O
II
(x,
O
co
w
cq
t-H UAONt— 03
t- O LAOO t— f—
EH M
« «<
W PH
>•
O
O M
EH
W
u <;
S CO
co co
t-l M
P
co
c--
S5
O
EH
CO
CO
W
O
o
^ co
O >H
M O
EH
CJ
W
i-3 O'
iJ W
O
CJ>
f\J(AJOJ(AJ
HiHHH
a >3 c >» c >> >•, >, :>>>-, a
rH H.H
CVI
o
W
pq o Q
H H H rH
-------
-205-
(i,
o co
W
V, O
W ^)
m «
fe E-1
H O
EH M
o
EH
O M
EH CO
O <;
£5 CO
<; o
EH fL.
CO CO
M M
P Q
O
CO
« EH
EH CO
O K
o 5
a co
O >H
M O
EH S
O W
w s.
iJ Or-
^ W
O «
O ft,
---
r\j c\j oo —^^c^l^r^r^r^o^o^oo^o^OfY^ vo
UAVQCOCO t— f— t~- t— ^ t^-Lr>onPOLr\Lr\c\) O.J C\J
a a c
rH CM
CM OJQOOO CM cvj CM
r-H H rH H rH
a a
rHrHiHr-HrH
rHr-H
onoocviojmoncMCMCMCMooojcvionoocviCMCXi
f— CO ONO HOJ OO^f LTNVD t— CO a\ H Ol f)
C\JC\JCMC\JC\JC\lOJC\JC\JC\J
-------
-206-
RUN
NUMBER
1
2
3
U
5
6
7A
7B
1C
7D
7E
8
9
10
11
12
13
Ik
15
16
17
18
19
20
21
22
23
2h
25
26
27
28
29
31
32
33
WEEK'S
TONNAGE
151*1*.
1538.
1539.
1533.
1537-
151*3.
1537.
1533.
1538.
1530.
151*6.
1530.
151+7.
153U.
1536.
1533.
1550.
15U5.
151+3.
1538.
15^3.
1527.
151+0.
1536.
1539.
15^5 .
1537.
1537.
15U3.
839.
703.
1538.
151*7.
1*32.
561*.
51+3.
TOTAL
COST $
17,106.
22,157.
18,178.
23,118.
16,21*7
16,622.
17,H90.
17,362.
17,532.
17,260.
17,558.
17,683.
16,1*80.
19,222.
17,652.
20,1*20.
15,960.
ll*,61*3.
17,205.
15,81*7
16,1+61
16,3^8
17,899-
17,886.
15,870.
16,01*2.
16.U33.
16,239.
17,501.
9,289.
7,33U.
17,1*21*.
17,796.
5,226.
5,665.
6,678.
COLLECTION
$/TON
9.08
9.73
9-03
9.81
9-76
9.81*
9.72
9.8l
9.01
9-75
9.06
9.81
9.0l*
8.97
9-09
9. Ol*
9.79
9.18
8.36
9.82
9.86
9.ll*
7.73
9.81
THAN SFER
STATION
$/TON
2.00
2.08
1.51*
1.57
1.57
1.1*6
1.56
1.55
1.61*
l.7l*
1.23
1.31*
1.27
1.1*2
1.60
1.53
1.55
1.90
2.07
1.51
1.61*
2.97
2.3?
2.1*8
TOTAL
$/TON
11.08
lU.Ol
11.81
15.08
10.57
10.77
11.38
11.33
11.1*0
11.28
11.36
11.56
10.65
12.53
11 . 1*9
13.32
10.30
9.1*8
11.15
10.31
10.67
10 . 70
11.62
11 . 65
10.31
10.38
10.69
10.57
11.31*
11.08
10.1*3
11.33
11.50
12. 11
10.05
12. 30
TABLE E - 2
-------
K
O
g
oncocr\ononc—_=fCMonvDrHrHt—voON-ot^-o
_=r on on on j- -=r ononononononon CM CM ononj-
o
on H VD VD
\j- cMcoLArHJ-t^o\ocoo^on
LALArHOJOJLACMrHCMrHonHH-3 CO O\ OJ rH
rHrHrHrHHrHrHrHrHrHrHrHrHHH rHrH
V,
O
CM-^-S-^tLALALAVO-^tVO-^J on LA OJ LA J
rH rH rH rH H rH rH rH rH iH H rH rH rH rH rH rH
C_5pq CO_S-CMCMtr— OxCMHCMrHCMLAt^COOJVOCOO
W< VDVDVDVDVDVDVDVDVDVDVDVDVDLAVDLAVDt—
i-l
O
P-H
O
rHJ-LAVDrHHLAVDVDVDLAonOJOAVOrHrHOx
OJOJCMOJOJOJCVICMOJOJOJOJOJOJOJOnCMH
O
M
EH
O
w
o
o
O CO CTv Os O O O^ CO CO t- O\ H O\ OJ oo en O VO
VD on LA on VD LA LA LA LA LA LA LA LA j- LA _-t VD LA
W
FQ
rH oj on j LA vo
W
t— co cr\ o rH CM on _j
rH rH rH r-1 r I
-207-
M
r/j
co
O
PL,
CO
M
P
LA on _=r CM LA on -=t
LA.
on LA on _3- on LA j-
CM
o
E
o
o
M
P^
Pn
-=t Lr\c\JCMJ-^-CMCMOJOJOjon_crvDOjm-^-rH
rHonrHonrHOJrHHHrHrHCMHA|rHOJrHCM
H
f'1
1-1
m
-------
-208-
w
o
ffi
is;
M
§
CO
o
oj
ir\ t— m t— oo vo cvi oooot— OJCD
HHrHrHHrH H
HiHHHHrHHrHHHHCMHtHHCVJHCM
p
w
OJl/\V£)OJOOLr>L/NCn
VJD VO VO V£> V£> VO VO VO
o
o
OJOJOJCXJOJOJOJOJOJOJOJOJOJOJOJOJOJOJ
OJ
H
o
OJ
w
PH
OJ
w
K
o
tc
c
O3
o
PH
CO
O
OJOO t~t--3--^t-3-^}--3-^t CM iH
rHrHOJOJOJOJrHrHrHHrHrH
on
M
M
HH1
m
n
iHrHHHrH
O
o
W
0
O
UAVDVJDVOMDVO LrNLTNMDVDVD
^5 M
^ipq
LT\VDt--COO\OrHC
iHrHrHr-HiHOJOJOJOJOJOJOJOJOJOJroonoO
-------
-209-
NUMBER
OF
RUN TRUCK
NUMBER BREAKDOWNS
1
2
3
1*
5
6
TA
TB
7C
TD
TE
8
9
10
11
12
13
ll*
15
16
IT
18
19
20
21
22
23
2h
25
26
27
28
29
31
32
33
0
23
2
22
1
5
2
1
1*
0
0
7
3
9
2
12
0
3
1
0
5
10
10
10
0
2
2
2
2
0
0
0
3
0
1
0
NUMBER
OF
TRUCK
TRIPS
1*11
1*52
1*08
1*75
Ull
1*10
Hl2
1(08
1*08
1*07
1*15
1*22
1*17
1*35
1*06
1*56
U15
1*09
H15
Ull
1*17
l*ll*
1*1*1*
1*1*0
1*07
1*10
1*10
lao
l*ll*
229
191
1*08
1*16
119
153
11*5
TRUCK TRUCK
MILEAGE MILEAGE
IN IN
COLLECTION TRAFFIC
202U
2039
3083
31H9
1956
1962
3071
3071*
3118
321(9
3137
3105
2053
2053
3200
3198
1996
2020
31'47
3031*
2003
1978
3091*
3020
2065
2103
2005
20U3
3039
13 1*0
805
3155
29l*l
668
1*35
982
181*7
21696
1835
22800
181*1
6560
1857
1839
18)»5
1835
1871
6752
1875
13920
1833
ll*592
1866
3272
1882
3288
7506
71*52
7992
7920
1819
181(0
1826
18P8
1861
765
1*00
1838
1883
330
380
527
TOTAL
TRUCK
MILEAGE
3871
23735
1*918
2591*9
3797
8522
1(928
'i903
1*963
508>(
5008
9857
hg?B
15073
5033
17790
3862
5292
5029
6322
9509
9!*30
11086
10920
388U
391*3
3831
1871
1(900
210 '3
120S
1|993
)i8PU
Q98
815
1509
TABLE E - 1+
-------
-210-
RUN
DAILY WEIGHT, TONS
NUMBERS MONDAY
1
2
"J
J
k
5
6
7A
7B
7C
7D
75
8
9
10
11
12
13
1U
15
16
17
18
19
20
21
22
23
2)4
25
26
27
28
29
31
32
33
C/W =
TS? =
298
288
335
336
299
289
336
337
33k
330
3^0
325
301
29 k
336
329
302
301
336
33^
295
288
338
3k2
298
300
302
295
338
162
136
332
336
88
111
109
Collections
FRIDAY
222
220
222
22k
222
218
221
222
227
227
221
220
225
220
225
218
219
215
225
221
221+
221
22k
22k
22k
226
222
221
223
121
102
222
225
6k
3k
78
per week
Transfer Station, Yes
DAILY COSTS, $
MONDAY
3^02
kOOQ
3302
k221
3137
3k78
309k
311.0
32U2
31^9
3088
3115
318U
35kk
3258
3575
2957
2873
3210
29^3
3112
3057
320k
3167
3021
3072
3132
3111
3231
1872
1318
3071
3U60
1181+
1089
])+68
or No
FRIDAY
2509
321+6
2968
3705
2383
2293
2912
2828
2911
2833
2892
2931
2518
2813
2891
331+0
2H30
2028
2737
2520
2396
2371+
291^
2960
2306
231+0
2kl9
23k6
28l6
1289
1068
2890
281+2
7H2
856
98H
C/W*
2
2
3
3
2
2
3
3
3
3
3
3
2
2
3
3
2
2
3
3
2
2
3
3
2
2
2
2
3
2
2
3
3
?
2
2
TS?*
Y
N
Y
N
Y
N
Y
Y
Y
Y
Y
N
Y
N
Y
N
Y
N
Y
N
N
N
N
N
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
TABLE E - 5
-------
-211-
CO
^
0
M
M
(1)
O
o
o
EH
O
M
Q
h-i
g
EH
!^
1 — 1
IP
l-^.
CO
M
w
&
EH
EH
^
1 — 1
EH
ft,
O
Ptl
O
<"i
S
w
o
K
M
fi(
OJ
H
§
* — )
O'
t—
rH
B W
P^i t^
cy
OJ
w
ft
LTN O'
S H
PI
W
S
> — )
O'
OJ
P>q
1
O
OO
tt- \ 1 1
tt PT1
s
£3
0
01
M
ft
rH O
B rH
PH
PI]
R
1 1
0'
OJ
CO O CO LTN £3
CO LTN LTN O O O P^l
VO OJ D
0'
w
t—
rH
,~t 00 H rH rH p prl
CO CO rH Ol O O ' Pi
LTN OJ rH t)
O'
OJ
t- rH -t 00 W
VO VO VO O O O W
vo 01 p t>
r- O'
B H
pc;
O -* ON UTN OJ P^l
1 .
H ON l>- rH O O W
VD Ol t)
O
OJ
-3" O OJ OO rH W
VD I/A t— rH O O W
VO OJ PD
o o
t—
f~> ^
_^ LTN co OJ H K P>q
ON t— ON 00 O O W
LTN OJ E3
O'
OJ
CO rH CO OJ rH pel
_d- I>-VO rH O O PL]
VO OJ PQ D
t- O
B rH
PI
OJ -dr O\ O J" P3
O VD ON fi O O W
VD OJ t>
O'
CO
CO 0 W W
cq W W pn o o
S U O K ^3 t>
O t3 tD EH K K
D K PI EH EH
EH " W P5 W
W O K D >
O £3 fe ffi O H
^ O EH EH PT, PL,
OJ
oo ON oo LTN pq
t-— VD LTN O O O W
VD oj b>
o
LT\
H
rH
VD OO CO OJ H <~> pi
O ON CO rH O O EL|
VD 01 b
O
OJ
rH VD CO OO VO pt-T
Ol VO CO H O O M
VD oj oo ^3
rH 0'
grH
PI
-tf VD OJ VO H p:|
LT\ OJ rH p
O'
Ol
VD OO ON rH M
VO 00 CO rH O O H
VO OJ D
H Cff
rH
f^H , 1
t— rH -^f ON K PI!
OO _* O rH O O f£l
VO OJ rH f
O
Ol
LT\ O OO O OO pi4
VD VD vo rH o o ti
VD oj 1:3
ON O
!__
B H
K
OO ^t VD rH VO pj|
o t- ON oj o o PTJ
VO OJ ^D
o
CO
W co co
co cj S-1 W
co W W |r> cj o
S^ Cj O PM 113 j — )
CJ D ^3 FH K (r,
ZD K, K R EH
K EH EH fxj
C) r^\ 2* P^t CT-) 1 — \
£~, O EH EH P>H fn
f— oo ON VO
OO VD t-- rH O O
VD OJ
t- O ON on Ol
O~v VO O OO O O
L|-\ Ol rH
O ON OJ on rH
1/N LT\ CO O O O
VO OJ
t^- OJ rH CO OO
OJ LCN O H O O
VD OJ rH
O OJ O ON
OJ CO CO rH O O
VD oj
t— OJ rH CO OJ
o\ t— o oj o o
LTN OJ H
OO ON OO t— OO
LO J- t--- H O O
VD CM
OO VD ON rH rH
t-- o co oo o o
l/N OO
CO
Si to ui
co t. > s: si
ro N"! Si r") t i o
W o c ) p , ;- ) ;o
o in r~J I- < P; P,
p P, P, r i r i
K EH E i M
EH M pr; [•!
w o PI r:) l-
o h s; tn o i- 1
3 CD E-i EH P-.-, PI,
O)
<+ 1
o
r-|
vo
t
P'l
P'l
1
1 — 1
S!
CH
-------
-212-
vo
OJ
p
«
CO
J^
o
EH
Q
O
Q
0
EH
g
M
M
W
EH
fe
1 — I
rH
[S
CO
S
§•
1
S
§
EH
t^H
0
W
C5
FH
S
H
o
PH
w
PH
on
CvJ
g
ft)
OJ
OJ
s
K
rH
OJ
t^
b
K
CM
W
H
5
G?
H
w
*~3
H
5
O1
CO
•
OJ
CO
on
•
LTN
t-
00
H
B
5
O'
rH
W
5
b
o
CO
vo
vo
oo
o
vo
CM
w
5
b
O'
H
W
S
p
O
OJ
w
5
b
0
, — i
g
P
b
o
o
ON
•
ITN
rH
on
•
OJ
CM
O
vo
CM
-=*
CO
CM
O
on vo
vo
on
0
rH
VO
VO
OJ
CM
on
vo
OJ
ir\
t—
OJ
on
•
H O O O
H on
• •
CM O O O
ON OJ
VO O O O
r— vo
ON H O O
0 0
0 H 0 O
(r\ ON
0 CM 0 O
r-f
U\ O
LT\ rH O O
OJ
W
P
t^
QJ"
rH
on
H
g M
PH t~^
H
p
cy
C7N
•
H
O\
rH
•
on
00
OJ
w
w
ON P
CM O'
b rH
K
W
§
b
o1
on
H
•
CO
vo
•
vo
H
J-
u~\^t
vo
H
H
vo
CM
W
m
b
co a?
CM
g H
K W
W
J — 1
a?
CM
W
S
t — P
CM <3>'
^*
£3 >~~1
A<
vo vo on on w
ON CO
LTN
CO
1
o
CM
j^--j
1
g
0
O rH O O
H
CO
W CO CO
CO O W W
W p o o
o p^ p p
P EH K K
K EH EH
EH W
WWW
0 g p >
5= ta O H
EH EH (i. fe
W
O'
-d-
OJ
on
j-
OJ
OJ
on vo
vo
H
o
vo
OJ
t—
CO
OJ
vo
t—
CO
W
o
o
OJ
CO
LfN
OJ
CO
OJ
rH
rH
OJ
OJ
W
o
p
K
g
O
0 O 0 0
CM
•
O O O O
on -j- c-
t- OJ O O
on OJ oj
o on H o
rH
OJ
OJ ON on pq
CO H O O W
£^J
on cs"
on
& rH
VO rH -=f K W
o on o o w
i — i b
o
CM
W
O O O O W
CM b
on o1
t?*]
5 (H
pn
b- W
rH O O O fi I
| >
09'
ON O
CM t-- O O O O
ON
CO ON on
OJ VO O O O O
CO rH
VO -^
ON O O O O O
CO rH
ON LTN VO
J- -J- O O O O
^- CM
CO en
!ii CO CO W t/j t/j
CO O t^H p^t W C_) NH h^<
WPOO COWWPOC)
O K p P W O O K P P
prHKK 0 p p EH p-, &',
K H EH p or; PS EH E-<
EH W fc EH EH W
WWW EH M m W
OKP> HOKP^
£Z ffi O H O K fe W O M
EHEHpdPm SOEHEHfiHli,
, ^
CM
C^i
O
CM
VO
1
I'l
M
PQ
EH
-------
-213-
RUN
NUMBER
1
2
3
it
5
6
TA
TB
TC
TD
7E
8
9
10
11
12
13
lU
15
16
17
18
19
20
21
22
23
2 It
25
26
27
28
29
31
32
33
NO. OF
TRUCKS
2U
39
30
U6
2U
28
30
30
30
30
30
3U
2U
35
30
U2
2H
25
30
30
29
29
36
36
?U
2U
?U
2lt
30
13
10
30
30
7
8
9
TRUCKS '
MINUTES
AT DISPOSAL
AVE . MAX .
8.3
6.1
7-8
6.1
7.'4
5-9
7.6
8.1
7.9
8.9
7-3
5.8
8.0
6.0
8.2
6.0
8.2
6.0
8.5
6.1
5.8
5.8
5-7
6.0
7.8
8.5
7-9
5.8
6.1
6.7
6.2
8.7
8.8
6.2
6. H
5.7
26
12
28
12
23
12
21
29
23
32
21*
12
2k
12
23
12
26
12
36
12
12
12
12
12
25
23
30
12
12
19
21
21*
33
12
13
12
GETTING INDICATED
NUMBER OF OVERTIME
HOURS DURING WEEK
ONE TWO TWO
15
It
lit
18
ll*
18
12
ll*
13
19
12
7
12
5
lit
19
11
20
2 U
16
15
16
12
11
10
12
10
7
10
7
7
11
10
3
3
1
7
U
13
3
3
2
7
2
6
6
9
0
3
5
1*
8
7
7
6
7
5
8
6
2
3
5
7
0
7
0
H
5
8
o
r.
1
p
3
It
1
H
5
6
0
o
3
3
It
2
3
0
7
5
)t
6
5
3
7
6
3
5
0
14
3
It
3
It
1
U
6
p
0
7
TABLE E - 7
-------
-214-
ra
W O
fc ;=)
CD K
fe; EH
< ro
K
EH Q
H
EH
fe H >H >H
>t
W
co co VD l>- t — t— oo oo t-— t— u\ if\ on LTA LT\ vo co
vo or^ on on
oo on on oo oo ro oo -^- CM oo CM c\j on on on c\i aj CM - 1 01 ai CM
<$ PQ O O W
rH ""I tl~\ t- t— t— t— t— ON H OO LT\ H CM OO _^ LA VQ t - CO O\ r-l CVI OO
Hi-Hi—lOJOJOJOJOJOJCMCVJCMOOOOOO
-------
-215-
K O
O
H CM oo ~-i u\\o t— n\ r-\ c\i
H r-H i-H OJ OJ OJ OJ OJ CM C'J (M OJ r»") OO
o-.
-------
-216-
K"-l
m
w
M
F<3
5
o
£5
M
K
B
C/3
PH
M
PS
EH
P"H
O
K
W
FQ
§
^
K
W
-i
i — i
M
<
&
EH
r-l
OO
O
CO
O
c-
00
t-
l>-
c—
VO
t—
ir\
t-
-3-
t—
CO
t-
OJ
t-
rH
t-
CK
0
H
O
<
P
EH
LTN
LTN
-3"
U"N
00
LTN
CVI
tA
rH
LA
K
^ te
H3 M
§
1 1 1 1
1 1 1 1
1 1 1 1
1 1 1 1
1 1 1 1
1 1 1 1
00 LfN 1 1
1 1
CO VO 1 CM
1
H ON CM t—
rH
rH CM OJ CM
r-l rH rH rH
-H/ OO LT\ J-
rH H H rH
J- -4- oo VO
rH rH i-H rH
-d- LTN o ON
rH H OJ H
LTN LTN CM O
rH rH CM CM
1 -3- 1 1
1 rH 1 1
1 VO 1 1
1 rH 1 1
CM CO VO VO
r\j r-l CM oi
OJ O VO CO
OJ C'l rvl Ol
LO rH U-N VO
CM oj oo oo
<
rH OO LTN f—
1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1
1 1 rH rH 1 1 1 1 1 1
II 1 1 1 1 1 1
CM H OJ OJ OJ OO 1 1 1 I
1 1 1 1
-3- VO t-- LTN ON ON 1 1 1 1
1 1 1 1
i-HOJOOCMHrHOOOO 1 rH
H rH rH rH H rH I
-^-^--^J--^--^!^-^- Ivo
rHrHrHrHHrHrHrH 1
OOt-^VOVOVOONOrHOJ
HHrHrHrHrHHOJrHrH
C3NONt~-OOOOoO OJJ-OOJ-
rHrHrHrHrHrHOJOJrHrH
OJ O OOJ ONONVOOOOVO
CMCMCVICMrHrHCMCMCMH
1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 OO 1 1 1 1
1 1 1 1 1 rH 1 1 1 1
t— VO t~- t— LTN O\ It—- 1 1
CM CM CM CM CM rH 1 rH 1 1
OO OO £^- CO CM ,-i OO rH OJ CM
CM CM CM Ol OO CM J OO r-l CM
LA LTN ^f lTv(MO\t--rlt-i~-
O"l OO OO O") OO CM -^ -J- OO CM
pq 0 o M
t— t— t-t~-ONHOOLArHCM
r-l H rH Ovl CM
1 '
, ,
1 1
, ,
1 1
1 1
1 1
1 1
1 1
1 t-
1
1 rH
1 rH
ON _3
rH
rH t—
r-l rH
_H/ O\
rH rH
LT\ rH
rH CM
1 1
1 1
I 1
1 1
O VO
rH CM
vo !"--
r 1 (M
OO U)
OJ m
OO ,-t
Ol CM
1 1 1 r 1 1 1 1 1
III III!
1 1 1 CM 1 1 1 1
III 1 1 1 1
1 1 1 CM 1 1 1 I
III 1 1 1 1
rH 1 | CM 1 1 1 1
II 1 1 1 1
CM 1 1 VO 1 1 1 1
II III)
t- 1 1 VO LA 1 1 1
II III
rH rH 1 t- O 1 1 1
rH 1 rH 1 1 1
-CT OO OO OO ^3 \ 1 1
rH rH i-l 1 1 1
t~- CM O IA VO -3 OO r-
rH rH rH rH r-H
ON OO CM VO rH ON H CM
rH rH rH H CM H rH
ONLr\VOON_3 rHOOOO
rH rH H rH CM r-1 r-l rH
1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 t
1 1 1 1 ~J 1 1 1
1 1 1 1 rH 1 1 1
CO | | I CO 1 1 1
CM 1 1 1 r 1 1 1 1
OO CM IA OO ir\ - J 0 O\
CM CM i 1 . 1 CM i-H
.- 1 t VO VO OO C > 'M (v)
f) CM CM - J CM CM 'M (>l
LA VO t— Of) O\ r-) (M OO
Ol OJ CM CM CM OO OO (')
O
i-H
1
W
M
i-l
m
•-3\
n
-------
-217-
BIBLIOGRAPHY
American Public Work Association, Committee of Refuse Collection and
Disposal, Special Report No. II, Refuse and Disposal Practices/
Chicago, 1950.
American Public Works Association, Proceedings, 57th Annual Public
Works Congress in Detroit, Chicago, 1950.
American Public Works Association, Municipal Refuse Transfer Stations,
APWA 1962 Yearbook, Chicago, 1962.
American Public Works Association, Committee on Refuse Collection,
Refuse Collection Practice, Chicago, 1966.
Black, Ralph J . et al ., Refuse Collection and Disposal, An Annotated
Bibliography, 1962-1963, U.S. Department of Health, Education,
and Welfare, Public Health Service, Washington, D. C., 1966.
Bonini, Charles P., Simulation of Information and Decision Systems in
the Firm, Prentiss-Hall, Inc ., Englewood Cliff, N . J ., 1963 .
Bowerman, F.R., Engineer Discusses the City Transfer Station, Refuse
Removal Journal, New York, Jan., 1962.
Bundy, George, ^lovel Refuse Transfer Station, The American City,
New York, June, 1961 .
City of Baltimore, Department of Planning, Population and Planning as
Related to Baltimore City, Baltimore, 1964.
-------
-218-
Cole, Earl E., The Same Services at Less Cost, The American City,
New York, August, 1960.
Conway, R .W ., Some Tactical Problems in Digital Simulation, Manage-
ment Science, Vol. 10, No. 1, Baltimore, October, 1963.
Engineering Foundation Research Conference, Conference Preprints: Solid
Waste Research and Development, New York, July, 1967.
Flagle, C.D., W.H. Huggins, and R.H. Roy, Operations Research and
Systems Engineering, The Johns Hopkins Press, Baltimore, 1960.
Forester, J .W., Industrial Dynamics, M .1 .T . Press and John Wiley and
Sons, Inc., New York, 1961.
Griffin, Sidney F., The Crisis Game Simulation International Combat,
Doubleday and Co., Inc ., Garden City, N . Y ., 1965.
Hope, M.C., C.C.Johnson, and L. Weaver, Refuse Handling Practices
in the United States, Public Health Reports, February, 1965.
Hufschmidt, Maynard M. and Fiering, M .B , Simulation Techniques for
for Design of Water Resource Systems, Harvard University Press,
Cambridge , Mass ., 1966.
Jennings, N .H . and Dickens, J .H ., Computer Simulation of Peak Hour
Operation in A Bus Terminal, Management Science, Vol . 5,
No. 1, Baltimore, 1960.
Karolevitz, Bob, Transfer Stations Replace Limited Maintenance Dumps,
Public Works, Ridgewood, N J ., April, 1963.
-------
-219-
King, Maurice M., Transfer Station Saves Santa Monica $60,000,
Refuse Removal Journal, Mew York, November, 1962.
Koch, A.S., County Plans a Master Plan for Refuse Disposal, Public
Works, Ridgewood, N.J., August, 1960.
Los Angeles County, California, A Report to the Directors of the County
Sanitation Districts, September, 1955.
Maass, Arthur, et al ., Design of Water Resource Systems, Harvard
University Press, Cambridge, Mass., 1966.
Morschaurer, Joseph, III, How to Play War Games in Miniature, Walker
and Co., New York, 1962.
Muckelroy, Ed F ., Hauling Units Govern Design of Refuse Transfer Station,
The American City, New York, June, 1962.
Ohio Department of Health, Proceedings: Technical and Planning Aspects
of Solid Wastes, A Short Course, Columbus, Ohio, Sept., 1965.
The Organization for European Economic Cooperation, Collection and
Disposal of Town Refuse Street Cleaning, Paris, May, 1953.
Quon , Jimmie E ., et al ., Simulation and Analysis of a Refuse Collection
System, Journal, Sanitary Engineering Division, American
Society of Civil Engineers, October, 1965.
Scheiling, Thomas C., The Strategy of Conflict, Harvard University
Press, Cambridge, Mass., 1960.
-------
-220-
Sprowls, R. Clay and Morris Asimow, A Computer Simulated Business
Firm in Management Control Systems, ed . Donald Malcom and
Alan J. Rowe, John Wiley and Sons, Inc., New York, 1960.
Taylor, R .C ., Modern Refuse Demands Modern Collection Methods,
American City, New York, Sept., 1955.
Tocher, K., The Art of Simulation, The English Universities Press, Ltd.,
London, 1963.
Tocher, K., Review of Simulation Languages, Operational Research
Quarterly, Vol. 16, No. 2, London, June, 1965.
University of California, An Analysis of Refuse Collection and Sanitary
Landfill Disposal, Technical Bulletin No. 8, Series 37, U.
of C. Press, Berkeley, California, 1952.
University of Michigan, School of Public Health, Lectures presented at
the Inservice Training Course in Garbage and Refuse Collection
and Disposal, Ann Arbor, Mich., 1947.
Weaver, L., Refuse Collection and Disposal, An Annotated Bibliography,
1954-1955, U.S. Department of Health, Education, and Welfare,
Public Health Service, Washington, D. C., 1956.
Zimmerman, Richard E., A Monte Carlo Model for Military Analysis,
Operations Research for Management, Vol . II, Ed . by Joseph
McCloskey and Johns F . Coppinger, The Johns Hopkins Press,
Baltimore, 1956.
-------
VOLUME I
-------
-------
TABLE OF CONTENTS
Part 1 User's Guide to the Simulation
Model (Model 3 of Volume l) 1
Part 2 FORTRAN IV Coding of the Simulation
Model 25
-------
-------
-1.
PART 1: USER'S GUIDE TO THE SIMULATION MODEL
USER'S GUIDE TO THE JOHNS HOPKINS
SOLID WASTE COLLECTION SIMULATION MODEL
The report resulting from the preparation of the simulation
model is composed of two volumes. It is recommended that both be
available to the prospective user. The user of these programs
can realize the full intended simulation potential by adjusting
the values of model data and policy variables, which are grouped
in two locations in the program. These locations are:
(1) The next to the last card in the entire program upon
which are punched nine variable values, e.g., collection frequency,
which control system policies to a large extent. This card is
termed the System Control Card. (RUNDAT discussion, pages 93-95,
Vol. 1)
(2) The BLOK DATA subprogram, in which the user puts the
great mass of physical characteristics of entities in the model,
the field characteristics of the simulated system, and the costs
to be associated with different activities. Examples are the col-
lection truck capacity for the first, the distribution of truck
dumping time for the second, and daily pay of a driver for the last.
(BLOK DATA discussion, pages 33-36, Vol. 1)
Both of these control areas, the System Control Card and the
BLOK DATA subprogram, are explained in detail in following sections
of this Guide.
-------
-2-
The five following sections discuss the information which is
given to the program:
(1) Major system environmental conditions and policies.
(2) System Control Card.
(3) Geographic information in BLOK DATA subprogram.
(4) Field performance information and costs in BLOK DATA
subprogram.
(5) Computer requirements and output.
-------
-3-
Sj|c t ip n_ 1
MAJOR SYSTEM ENVIRONMENTAL CONDITIONS AND POLICIES
The extent of the studies of which the model is capable and the
investigation which was made of proposed changes in the Baltimore
system are discussed in detail in Volume 1 (pages 12, 76-88, 115-116,
139, and 145).
Summarizing these complete discussions, a single run on the com-
puter can simulate a collection system with the'following control
by the user:
(1) The trucks carry the refuse directly to a disposal site
with no transfer station (Model 3A); or, the trucks carry the refuse
to a transfer station with an unlimited number of unloading docks
and with tractor-trailers for transport of the refuse to a disposal
site (Model 3B); or, the trucks carry the refuse to a transfer station
with two unloading docks and with tractor-trailers for transport of
the refuse to a disposal site (Model 3C).
(2) Collection frequency may be either semiweekly or triweekly.
(3) Truck volumetric capacity may be varied.
(4) Truck minimum loaded weight may be varied.
(5) With reference to the number of household units making up
a daily task assignment for a truck, the model equations generate
assignments which average about 6.5 hours per day for 20 cubic yard
trucks.
-------
-4-
(6) Rates of pay and overtime pay to labor may be adjusted.
(7) Location of the disposal site and routes to it may be
varied.
(8) Location of the transfer station, if any, and routes to
it may be varied.
(9) Trailer volumetric capacity may be varied.
(10) Trailer minimum loaded weight may be varied.
(11) The option exists of auxiliary compaction apparatus at
the transfer station.
(12) Equipment hourly charges may be varied.
(13) Permanent installation capital investment and amortiza-
tion may be varied.
(14) The real urban tract for which the model simulates a
collection, system may be bounded as desired by the user with a
maximum population constraint of approximately 300,000 people.
-------
_ c _
SectjLon___2
THE SYSTEM CONTROL CARD
The user is again referred to pages 93-95 of Volume 1.
Reference is also made to the model coding in the latter part of
this volume and the command indexed "0610RUND".
(1) Control variable 1, COLFRE, is the collection frequency,
which may be 2 or 3 times per week. The value, 2.0 or 3,0, is
punched in columns 3, 4, and 5.
(2) Control variable 2, ASSSUN, communicates which of the
three models, 3A, 3B, or 3C (pages 85-96, Vol. 1) is to be run.
The value are: 0.0 for Model 3A, 1.0 for Model 3B, and 2.0 for
Model 3C. The value must be punched in columns 8, 9, and 10.
(3) Control variable 3, ASSUNK, adjusts the number of house-
hold units assigned as a collection truck's daily task; the normal
value is 1.0. The variable appears in the command indexed
"07AOTB1". If ASSUNK is given a value less than unity, the number
of units assigned is decreased and vice versa. A value of 1.2
will increase the average daily assignment by 20%. Thus if a
truck smaller than the standard 20 cubic yards capacity is to be
in the model or if it is desired to reduce the average work hours
of the standard truck, the value would be set less than unity.
Likewise, if a truck larger than standard is to be in the model
*
Unless specified, each variable contains an imbedded decimal point,
-------
-6-
or if longer workdays are desired, the value would be set greater
than unity. The value is punched in columns 11 to 15, right justi-
fied.*
(4) Control variable 4, TRLHAL, and control variable 9, Q10.
If a transfer station is in the simulated system, Q10 is given
the value of 1.0 and TRLHAL is the one-way traffic distance in
miles between the transfer station and the disposal site, having
values such as 5.0, 18.3, or 27.9.
If no transfer station is in the simulated system, Q10 is
normally given the value of 0.0 and TRLHAL is the average one-way
distance in miles between the disposal site and the population
centroid of the urban tract under study. However, a refinement in
model usage is possible in this latter case. If Q10 is given a
value of 1.0 and TRLHAL set at 0.0, the model calculates collection
trucks' traffic distances from each of many subareas in the urban
tract. Section 3 of this Guide discusses this latter use in
detail.
In all cases, the value of TRLHAL is punched in columns 16
to 20, right justified. The value of Q10 is punched in columns
41 to 45, right justified.
(5) Control variable 5, RUNNO, is the User's run number; it
is expressed as 2.0, 17.0, etc. Its value is punched in columns
21 to 25, right justified.
*
right justified: the rightmost digit must be in the rightmost
column of the specified field.
-------
-7-
(6) Control variable 6, K, is an integer number which controls
the values of the pseudorandom numbers which are generated for
drawing from frequency distributions of stochastic events. A
different sequence of pseudorandom numbers is generated with each
different K. The value of integer zero, 0, is satisfactory for all
runs; however, the use of different K's for different runs on an
identical system will test response sensitivity to randomness.
The value of K must be integer, may be between 0 and 99999, inclu-
sive, and should be punched in columns 26 to 30, right justified,
without decimal point.
(7) Control variable 7, NOTRC, is meaningless if no transfer
station is in the simulated system; it should be given a value of
1 in column 35 in this case. However, if a transfer station is in
the model, NOTRC affects the number of long-haul tractors at the
transfer station. If NOTRC is set at integer zero, 0, a reasonable
number of tractors for assignment is calculated by the model. If,
however, the User wants to assign a certain number of tractors,
NOTRC is given the desired number between 1 and 10. The value is
integer, and is punched in columns 34 and 35, right justified,
without decimal point.
(8) Control variable 8, Q9, is the control for paying or not
paying overtime to collection truck personnel. No overtime is
paid if set equal to 0.0; overtime is paid if set equal to 1.0.
The value is punched in columns 38 through 40, right justified.
-------
-8-
GEOGRAPHIC INFORMATION IN BLOK DATA SUBPROGRAM
The urban tract must first be delineated into "census tracts".
These are relatively small, usually of less than 6,000 population,
and are established by the Bureau of the Census as basis for com-
piling census data. The population density in housing units per
acre for each tract and the number of housing units within each
tract must be tabulated. The former data are translated by the
user into one of four neighborhood densities (page 155, Vol. 1).
Having determined the census tracts' boundaries and household
density classification in each tract, a map termed the Model Map
is prepared. New residential subareas , formed by one or combina-
tions of several adjacent census tracts of the same density
classifications, must now be delineated and numbered.
A rectangular grid in units of feet is now superimposed on
the Model Map; the grid axis should parallel residential street
orientation, if such exists. The grid may be at any convenient
point. The disposal site and transfer station site, if any, are
plotted or referenced on the map, with their X and Y coordinates
(positive or negative) noted.
The population centroid of each residential subarea must be
marked and its coordinates noted. This is a matter of user judge-
ment, as many of the subareas will be irregular in shape and may
have localized housing interspersed with open areas.
-------
-9-
The collection trucks dump either at the disposal site or at
the transfer station; in either case, the probable traffic route
between each subarea centroid and the truck dumping site is deter-
mined by the user.
Four sets of information must be transmitted to the computer
in the BLOK DATA subprogram:
(1) Grid coordinates of disposal site and transfer station.
(2) Grid coordinates of subareas1 population centroids.
(3) Number of household units in each subarea.
(4) One-way traffic distances for collection trucks.
(1) The grid coordinates of the disposal site are entered as FX
and FY in the statement indexed "0650BLK". The grid coordinates
of the transfer station are entered as TX and TY in the statement
indexed "0750BLK". TX and TY should be given values of 0.0 when
Model 3A is run (page 81, Vol. 1).
Assume an urban tract for study is composed of five subareas
such that:
Subarea
number
1
2
3
4
5
Neighborhood
classification
1
1
3
2
4
No. of
households
9227
2472
10303
861
6917
Centroid X
coordinate
53000
57500
61500
50800
52500
Centroid Y
coordinate
64500
62500
64500
61500
62000
TABLE 1
-------
-10-
(2) The subareas population centroids are entered in the BLOK DATA
subprogram as values of AX1 in "0820BLK" and AY1 in "0860BLK". The
values of Table 1 would appear as:
DATA AX1 / 53000., 57500., 61500., 0820BLK
I 50800., 52500., 20*0./ 0830BLK
and
DATA AY1 / 64500., 62500., 64500., 0860BLK
1 61500., 62000., 20*0./ 0870BLK
It should be noted that all subarea statements in BLOK DATA have
space for data from 25 subareas. Only five subareas exist in this
example, thus the 20*0.0 completing the statement.
(3) The number of housing units in each subarea are entered as
values of ANOHUN in the statements starting with "0800BLK". Table
1 values would appear as:
DATA ANOHUN / 9227., 2472.,10303., 0800BLK
1 821., 6917., 20*0.O/ 0810BLK
(4) The one-way traffic distance for the collection trucks from
each subarea centroid to the truck dumping site is communicated to
the computer by the commands beginning with "0630TB1", which appear
AHALDS(I) = (ABS(AX1(I) - AX2(I)) + 0630TB1
ABS(AY1(I) - AY2(I)) +
ROADIS(I)) / 5280.
The choice of each subarea's route may be from three schemes
(pages 111 and 112, Vol. 1).
-------
-11-
Assume u subarea 1 has a Metric-L route only from its centrold
to the dumping site. AX2(1) and AY2(1) are given the values of the
dumping site grid coordinates (0840BLK and 0880BLK). ROADIS(l)
(1110BLK.) is set equal to 0.0.
Assume a subarea 2 has a truck highway direct from its centroid
to the dumping site. ROADrS(2) is given the value of the highway
distance' in feet, and AX2(2) and AY2(2) are set equal to AX1(2) and
AY1(2), causing the Metric-L distance in this case to be zero.
Assume a subarea (3) for which the trucks move along a highway
to a point "A" and then on a Metric-L path to the subarea centroid.
The highway distance in feet from the dumping site to "A" is entered
as the value of ROAD1S(3). The grid coordinates of "A" are entered
for the values of AX2(3) and AY2(3).
The statement for ROADIS information for this example might
appear:
DATA ROADIS / 0.0, 9400., 1720., 22*0.O/ 1100BLK
-------
-12-
Sectton 4
FtELD PERFORMANCE INFORMATION AND COSTS
IN BLOK DATA SUBPROGRAM
All variables listed in the BLOK DATA subprogram must be
given values for the model to run successfully. In some cases,
the value should be or can be zero, but the value must be entered.
Reference is made to statement "0610BLK" in BLOK DATA of the model
coding in this volume; the three variables, COMPAP, CONA, and CONB
are listed together followed by their three values simply as a
space saving device. The three statements could have been:
DATA COMPAP / 150000./ 0610BLK
DATA CONA / 40000. / 0612BLK
DATA CONB / 75000. / 0614BLK
The latter arrangement would have required three IBM cards rather
than the packed one. The variables in the subprogram and the
manner in which their values are presented are discussed below:
COMPAP - the capital investment in dollars (including
installation) of transfer station auxiliary compaction equipment;
this will vary over a wide range depending on the type and manu-
facturer (pages 110-114, Vol. 1). If compaction equipment is in
the model, the variable RIGMAX (0710BLK) must be given the value
of the minimum weight of the compacted load to be carried in the
trailers.
-------
-13-
CONA, CONB, COND, CONE, CONF - these five coefficients appear
in several model equations which express transfer station land
value and equipment cost as functions of station daily capacity.
The equations are indexed "1140TB2" and "1170TB2" for land value;
"1090TB2" and "1110TB2" for equipment and structure cost. For the
land values, "1170TB2" is applicable for stations with capacity of
200 tons per day or less; "1140TB2" is for stations with daily
capacity greater than 200 tons. For costs of station structures
and equipment, "1110TB2" is applicable for stations with capacity
of 100 tons per day or less; "1090TB2" for greater than 100 tons
per day. The user may change the affecting variables, if needed,
to fit his simulated system. Auxiliary compaction apparatus cost
is not expressed in these coefficients, but with the value of the
variable COMPAP.
CSHRTC - the hourly charge for tractor operation in dollars
for all costs of the tractor-trailer rig operation except the
driver's pay. The value includes fuel, maintenance, and amortiza-
tion both for the trailers and tractor. The charge is for time of
operation of the tractor; no charge is made against the trailers
per se. This varies with equipment size.
CSTHR - the hourly charge for collection truck operation in
dollars. This charge is for all costs of the collection truck
operation except the drivers' and laborers' pay; this includes
fuel, maintenance, and amortization. The charge is for actual
time of operation. This varies with equipment size.
-------
-14-
DELDEP - the model attempts to duplicate the activities at
a municipal garage as the trucks leave in the early morning. The
trucks normally do not all leave together, but rather depart over
a period of time. DELDEP is the increment in minutes between suc-
cessive collection trucks' departures. The user does not need to
change the value, set at 0.1 minute.
DRDPAY - Collection truck's driver's pay in dollars received
for a day's work, even if less than eight hours. If over eight
hours, the driver receives DRDPAY plus overtime hours times DROVRT.
DROVRT - Collection truck's driver's hourly overtime pay in
dollars (see DRDPAY).
FLTLTM - the off-route time in minutes charged to a truck
having a flat tire or breakdown. User's option as to changing.
FX, FY - the rectangular grid coordinates in feet of the final
disposal site.
IN - the number of input tape for computer installation.
This varies with computer installations.
IOU - the number of output tape for computer installation.
Varies with computer installations.
K1NTRK - the capacity in cubic yards of the compactor collection
trucks.
K1NTRL - the capacity in cubic yards of the long-haul trailers
working out of the transfer station.
NAREA - the number of subareas within the urban tract being
investigated. NAREA cannot have a value greater than 25. Each of
-------
-15-
tlu1 subareas is of a homogeneous housing density of one of the four
cJassifications. Varies with different urban tracts under study.
ONCE - the tractor-trailer rigs have a histogram for dumping
times at the final disposal site. It is a normal distribution with
a mean of ONCE minutes and a standard deviation of TRES minutes.
This may vary with the equipment type, but the results are probably
not over sensitive to the values.
OVPAYL - the overtime pay in dollars per hour for the collection
trucks' laborers.
PAYLBR - the pay in dollars per day for the collection trucks'
laborers.
Q5 - Overtime pay in dollars per hour for the driver of the
trailer-tractor rig.
Q6 - pay in dollars per day for the driver of the trailer-
tractor rigs even if less than an eight hour day.
Q7 - the tax revenue from the transfer station land which is
lost to the city because of the city's occupancy rather than com-
mercial or industrial occupancy; expressed in dollars per year.
Q8 - the trailers at the transfer station do not start getting
filled in the early morning until the collection trucks have had
time to make a trip out and back. The model therefore has the
tractor-trailer rig drivers report for duty later than the collection
truck personnel. This time lag in minutes is Q8; the one hour
value presently in BLOK DATA is probably applicable to most cities.
-------
-16-
R - the amortization interest rate for transfer station
structures and equipment; also the interest rate applied to the
transfer station land investment (page 114, Vol. 1).
RGVMAX - maximum speed in mph allowed the trailer-tractor
rigs in traffic.
RGVMIN - minimum speed in mph allowed the trailer-tractor
rigs in traffic.
RIGKA & R1GKB - the two equation coefficients in the least
squares equation, log1QV = RIGKA + (RIGKB*X), which relates trip
distances with trailer-tractor rig traffic speeds. V is speed in
miles per hour and X is one-way traffic distance in miles. After
the dependent variable, log,QV, is found from the equation, the
log of traffic speed is drawn from a log normal distribution which
has "log nV" as the mean and VELSGR as the standard deviation.
The command "0720RGO" then gives the true traffic speed. If a
new regression equation is desired for the User's locality, a
discussion with the city traffic engineer may suggest improved
equation coefficients. If the User decides to determine his own
coefficients, it is recommended that approximately 100 tractor
trips with varying trip distances be made. The least-square
regression of log speed on one-way trip distance can be calculated
and these coefficients and standard error of estimate, VELSGR,
determined. It should be noted that the equation is applicable
only up to a certain maximum distance "RMXDSR"; above this distance,
log V, normally found from the equation, has a constant value,
VELMUR. These two variables are given values in "0730BLK and 0760BLK".
-------
-17-
RIGMAX - the minimum net weight in pounds which the transfer
station trailers carry. Collection trucks dump individually, and
when the accumulated weight on the trailer exceeds R1GMAX, the
trailer is replaced by an empty one.
RKA & RKli - the two equation coefficients in the least-squares
equation, log V = RKA + (RKB*X), which relates trip distance and
collection trucks' traffic speeds. V is speed in miles per hour
and X is one-way traffic distance in miles. After the dependent
variable, log V, is found from this equation, the log of the
traffic speed is drawn from a log normal distribution which has
"log V" as its mean and VELSGT as its standard deviation. The
command "0680TRF" then gives the true traffic speed. As discussed
with R1GKA and RIGKB, the city traffic engineer may suggest
improved equation coefficients and standard deviations. New data
can be gathered and a new equation derived if desired. Again this
equation is applicable only to a certain maximum distance, "KMXDST";
above this distance, log V has a constant value, VELMUT. These
two variables are given values in "0730BLK and 0760BLK".
RMXDSR - see discussion on RIGKA
RMXDST - see discussion on RKA
STMFST - the collection trucks are assigned various amounts
of minimum off-route time which includes delays in leaving the
city garage in the morning, lunch time, and coffee breaks. These
off-route times increase from "STMFST" minutes for the first truck
to leave the garage in the morning by increments of DELDEP minutes
for each succeeding truck (page 29, Vol. l)
-------
-18-
TRES - see discussion on ONCE
TSLBPA - Collection truck laborer's daily pay in dollars.
TX & TY - grid coordinates in feet for the transfer station.
UTILITY - average monthly utility cost of transfer station
in dollars; includes water, gas, and electricity.
VELMAX - maximum average speed in mph allowed the collection
trucks in traffic.
VELMUR - see discussion on RIGKA
VELMUT - see discussion on RKA
VELMIN - minimum average speed in mph allowed the collection
trucks in traffic.
VELSGR - see discussion on RIGKA
VELSGT - see discussion on RKA
WATEZ - the net weight to which the collection trucks are
loaded before quitting collection and going to dump. This is a
function of the cubic yardage of the truck and the density to which
it packs. The 8700 pounds used in Volume 1 came from 20 cubic yard
capacity being loaded to 435 pounds per cubic yard (0770BLK).
Varies with truck capacity and type.
YRS - amortization term in years for transfer station struc-
tures and equipment (page 114, Vol. 1).
ANETYP - This is a subscripted variable for which 25 values
are possible of the neighborhood type of each of the urban tract
subareas. The example of Table 1 has only 5 subareas, so the
statement giving the values for column 2 of this table would appear:
DATA ANETYP / 1., 1., 3., 2., 4., 20*0.0 / 0800BLK
-------
-19-
AX1, AX2, AY1, AY2 - These variables have been discussed in
Section 3. The statements "0820BLK to 0890BLK" in the coding were
derived from Table 6-1 (pages 118-121, Vol. 1) and show the trans-
mittal of the data from the planner to the computer for the Baltimore
tract.
COLMLK - the average street footage per net acre for each of
the four neighborhood classifications. This varies greatly between
cities. The data statement for Baltimore in the coding reads:
DATA COLMLK / 550., 750., 875., 1000., / 0900BLK
This means COLMLK for neighborhood density classification 1 = 550
linear feet per net acre, COLMLK(2) = 750 linear feet per net acre,
etc.
CORACR - ratio of gross acres to net acres for each of the
four neighborhood classifications. This varies greatly between
cities and even within cities.
DAYS - This statement (0920BLK) should be left alone; it has
computer use in printing the proper values of days, such as MWF or
TTS, in the truck assignments of Table 2 of the model results
(page 79, Vol. 1).
NOTE:
The statements from 0930BLK to 1090BLK inclusive give values
for many frequency distributions (histograms) of field performance
information and area data. A discussion follows:
-------
-2U-
Assume collection trucks' incinerator dumping times in minutes
have been observed. The information is:
Time at incinerator
in minutes
2-4
4-6
6-8
8-10
10-12
12-14
Number of
trucks
4
5
12
2
1
1
25
% of
trucks
16
20
48
8
4
4
100
It is desired to put this table in proper form in the BLOK DATA
subprogram so that the simulation of the system also will have 16%
of its trucks taking 2 to 4 minutes, 20% taking 4 to 6 minutes,
etc. The statement which would transmit this information to the
model would appear:
DATA HISTD1 / 6., 2., 14., 16., 20., 48., 8., 4., 4., 7*0.0 / 1050BLK
The 6. is the number of time increments in data. The 2. is the
minimum value in the time range. The 14. is the maximum value in
the time range. The 16., 20., 48., 8., 4., 4., are the percentage
values of each of the time increments. The 7*0.0 is needed to com-
plete 16 bits of data as the model programming requires it (0510BLK).
The HISTK1 is the title for this histogram. The 17 sets of data
for model histograms are similarly prepared.
-------
-21-
HISC12 through H1SC44, (HISC"lJM)
are collection rates in pounds of refuse per hour by crews working
in neighborhood type "I" with "j" data since last collection. It
is noted that some are alike (0970BLK and 0980BLK). This is because
no significant difference was indicated between the two conditions.
If the user gathers any field information for his study, these 12
sets of data should have high priority as the model results are
sensitive to their values. Figures A-14 through A-18 (pages 174-176)
are plots of the distributions for these data.
HISTD1 - the histogram of collection trucks' dumping times in
minutes (Figure A-20, pages 182 and 183). This information is easy
to gather; the user should prepare his own.
HISTU1 through HISTU4 - distributions of housing units per net
acre for the four neighborhood classes. This will vary between
cities and should be prepared for each urban tract (Figures A-l
through A-4, pages 155-156).
PERUN - the average number of persons per housing unit for
the four neighborhood types. This must be given four values as
BLOK DATA is so programmed (0530BLK). If the user wants to use
the same figure for all neighborhood types, it must be repeated
four times, i.e.,
DATA PERUN / 3.0, 3.0, 3.0, 3.0 / 1100BLK
ROAD1S - this has been discussed in Section 3.
RKKA, RKBB, and RKCC - equation coefficients for the generation
of the number of households for a truck's daily assignment (0730TB1).
These will not be normally changed by the user.
-------
Section 5
COMPUTER REQUIREMENTS AND OUTPUT
The simulation model has been coded using FORTRAN IV. The
runs made at Johns Hopkins University were compiled and executed
under an IBSYS monitor on an IBM 7094 computer. The installation
consists of an IBM 1401 RAMAC system (used as a slave to the 7094),
a 7094 equipped with two data channels with eight tape drives per
channel, a printer, and a card reader. The Model should run equally
well on any electronic data processing system having a FORTRAN IV
compiler, an input/output device and at least 20,000 words or
equivalent of core storage.
An average run with a transfer station in the model required
the following times.
Compiler 2.55
Assembler 0.43
Loader 0.49
Execution 0.30
Utility 0.11
Total time 3.90 minutes
Approximately 8350 lines output and 250 pages are generated
when MAP instructions are included. Models without a transfer
station produce about 90% of the above.
-------
-23-
The "state of the simulated system" is not reported in time
increments as it occurs. The results which are printed (pages
77-84, Vol. 1) are summaries of the six-day week simulated activities
and costs.
The user submits the model deck of IBM cards to his computer
along with necessary lead cards which identify him, the account
to which the run is to be charged, and special instructions. After
the run is completed, he will normally get back the deck which he
submitted, another deck in machine language, a listing of the model
identical to that in this volume, and approximately nine pages of
results of his run.
-------
-------
PART 2
FORTRAN IV CODING OF
THE SIMULATION MODEL
-------
-------
c
(
(.
(.
(
(
r
(
c
C
(.
(.
r
t.
c
c
c
(.
(.
c.
(.
(
r.
c
r.
c
c
c
r.
c
(.
L
(,
c
e
c
r
c
(.
c
c.
c
r.
r.
c
c
(
c
r.
c
(.
t
r.
r
C
c
c
r
<
c
(,
(.
c
c
i
i
r.
c
r.
<
t
t.
c
r
(.
C
r
f.
c.
c
r.
(
c
r.
c
(.
c
r
c
c
c
c
r
S 1 MUI A II M i| I [) WASH MJI1M1IMN H!P A MTV ... T RU I T 1 » 196H
|!lf lull OWING AMI VAI'IAIIIIS USIO IN MIIUM THRfl
A'l II A 1 1 Y ( (IS 1 111 I S ,11 Ml 1 I 1 1 ', , AMOK T 1 7 AT ION, F 1 C
A'.', Slin A ( ON 1 MOl VA W 1 Al1, 1 f , WHF N - 0 , NO TR ANSI 1 R STATION,
WHIN 1 . , 1 S t NCI OUIUI . WHIN - ?., 1'. * 2 OUFUFS.
AASSUNINAI - NUMHI R IIE UN 1 1 S/ TRIJC K BY Rf Gfl F SS 1 UN F OUA T 1 UN
A( II 1 - l.l'l ',S At 1' 1 S
AI'AI DM '.A I HAIII IJISTANCI (I'llH ARfA NA
ANI T Yl' ( N A 1 - Nf I GHMOR Mill JO T Yl'f OF AHIA NA
AMII'UNINAI NUMIll II Nt HOUSING UN 1 1 S IN AREA NA
AM i< ii i ( n A } MiMur R nr «ou 1 1 ', WITHIN ARIA NA
ASMII'I 1 NA 1 - NIIMIII R III 1 IN 1 1 ', / A S S 1 r,NF 1) ID A TRUCK IN AREA NA
AS MINK A ((INSTANT HAVING VAIIIFS SUCK «S 0 . 1 5 UR l./O WHICH
HAIIII II Nil. Ill UN IIS ACIUAIIY ASSICNID TO NO. OF UNITS
(AHUIAlin IKI1M TMI K 1 (,l 1' 1 SS 1 UN F UUA T 1 UN
AX1INAI - X (.(Illlll) LNA II Ul CINIRUIU (IF ARFA NA
AX.MNAI X f riliul) INATF (II fINAI -POINT UN M6TRIC L HAUL PATH
AYIINAJ - Y ffllll/DINAff III CINTMUID UF ARFA NA
AY/INAI - Y 1 I'.UIill INATF Ul IINAI ITIINT UN HFTRIC L HAUL PATH
[\ - A slltt'.MU II VACtAHII DM II IN HldBAK t FNIPRN 10 COUNT
1 H Af 1 (,K', IWf H I 1 Mt .
(ft (-I-ST Ml (,miK,(U)N IHUIK GPfRATKjN PER DAY
( 1 K 1 M ( 1 IK.K T 1 Mr
(I'llHl - tdllKIIIIN IRIUUFNCY PER WFFK
((IIMH - I'lWItNT III Hit LILT ItlN IRUCKS WURKING 1 1 ME SPENT IN
(.01 1 1 (-1 ION.
CMMLK - RAIII) fll STREFT MMFAHE pfR ACRF BY NE 1 GHBORHOUU TYPES
f.(Hlf«/ - IIMI IN HINUTFS FIIK CULIECTING A S1NGLF TRUCK LOAD.
(TMPAP TOTAL (flST INCIUOIN', 1 N S T AL L A T 1 (IN OF AUXILIARY COMPACTING
IUIIPPIUI fflH IRANSffll STM10N
C(,NA- f I NS 1 AN IS
( f Nil APPl AH I NG
( r,N(. IN ( OUA I IONS
(. 1 , M, t 1 1 R
( I t,f TR ANSTFR MAT ION
( ( M - ANIi 1 AND COSTS
( IIRAI.IUM TYPI - RATIO or (,R(r,S ACHES TO NFT ACRES
(.('Mill (USI 01 OPfRATlNG (.1 II 1 F (. T 1 ON IRUCKS FOR ENTIRE WEEK
CfMNII VAI 0[ OF TRANSIIK STATION LAND
fniwl', N1IMH1 H (II Ml NtEXCI UDlNFi DRIVERS, STAIFINf, TRANSFER ST».
( U\l',i - NIIMIKR IN CllllFCrlUN IRIKK fRIW INCtUDINf, OR 1 Vtll
CSHRIC t/HR 1 OR TRACTOR T 1 Ml IN A(TUA1 DPI RATION
fSTHK - I/Ml) EOK CniLFCIION THOCKS EXCLUDING LABOR
f 1 ', - (.(1ST OF THANSFIR SIAIION t RIG OPERATIONS PER DAY
I.AYSIfOIIRi - 1..NDRI A MATRIX USED IN WRITING TABIE 2
WHK H APPEARS
NOR
I 2 3
COLFRE-1. 1 MUNTHU TUEFRI WEOSAT
? MHF TTS BLANK
IIAYSLf - DAYS SINCE LAST COLUCTION
DM Dl I' - TIME INTERVAL AT WHICH TRUCKS LEAVE IN MORNING (MINUTES!
DClAvf - AVERAGE, MAXIMUM, MINIMUM, + STND. DEV.
I,PTMAX - OF
I.CTMIN - COLIECTION TRUCKS TIME IN MINUTES
DMTSK, - AT TRANSIfR STATION
DIIKIIL- (OSI IN DDLl AHS/IIIN EOR COLIECTION TRUCKS OPERATIONS
IK, 1 IMG- (OSI IN DOLIARS/ION FOR TRANSFER STATION AND
TRAIl ER-TRACTOR OPERATIONS
101 ION- (.OSI IN DIHIAKS/HJN FOR ENTIRE OPERATION
lint IS - IIIIAI INVFSIMINI IN TRANSFER STATION LAND AND EQUIPMENT.
IIRIII'AY - IRIVIRS DAllY I'AY IN DOLLARS
DRIVHT (IRIVIRS OVIRTIMI PAY PFR HOUR
DSII - DAYS SINII IAST (OILFCTION
I,W - VARIAHll OSFI) III SI(,NA| DSPS1 OF NEW DAY — «0 EOR NEW DAY
IVIN1 - IYPI (IE IVfNT NIXI 10 HAPPEN TO COLIECTION TRUCK
IVINI 1 - IKUCK MAVIS YARD AND FNTIRS TRAFFIC
IVINT i - IROCK LEAVIS COLIHTION AND ENTERS TRATEIC
IVINT 't = IRUfK (EAVES TRAFrIC AND ENIER YARD
I Vt N 1 'i - ( Mljf K 1 N T 1 R S UJI
IVIM 1 IIIACIOR IRAIIIR R 1 (, HAVIS TRANSEIR S 1 A T I (IN
IVINI fl IRAflnR IRAKI H AI'R|VIS BACK AI IRANSEIR SIATION
1 INHAY - AN INUICAlllll IJSIO IKIWIfN RIGI1AK » DSPSI FOII INDICATING
II'AI A IKAIIIR IS IDLI « IDU , (F INDAY = 99).
IIAMO - IM'i.liAB II I T Y 01 A IH'IKOON OR FLAT TIRE FOR A SINGLE
TI-MIIC IRIP 101' COLLICTIMN IRUCKS.
IX - ' (IORIINAIE OF FINAI DISPOSAL SITE
IY - Y I.I (ii'DINAir (If FINAL DISPOSAL SITE
HI f 1 ?
HISC1) - HISTOGRAMS EOR DISTRIBUTIONS OF
HlSC!«i - COLLECTION RATES IN POUNDS PER HOUR.
HISC?? - THt LASI TWO NUMBERS IJ
H I SC?1 -
HISC2<. - REFER TO
HIST )? -
HISCil - I - NEIGHBORHOOD TYPE
HIS( I* - J = DAYS SINCE LAST COLLECTION
HI SCW -
MISC.'. 3 -
MISfAI. -----------__________
nn I M
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MA IN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MA IN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
U A 1 hi
-------
(
c
c
r.
c
c
c
c
c
c
c
r.
c
c
c
c
c
c
c
r.
c
r.
c
c
c
c
r.
r.
c
c
r.
c
c
c
c
c
c
c
c
c
c
c
r.
c
c
c
r.
r.
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
r.
c
c
f.
f.
r.
L
C
r.
c
r
r.
c
c
c
I'IMliI - Ml Ml, 1,1' ACS Mil' III!
M I S I ll/* - 11 I ', f R 1 [Ml 1 I 1 N S l.f
MISIIM - IKIU'.ING. UNI IS PER ACRF
ni MI)'. - IN riu <. NI iGni)URiio(ji) TYPES.
HISIUl - fill IK. THIN TRUCKS DUMPING TIMF HISTOGRAM. (MINUTESI
irriiu - (niiKiniN (RH)UTN(v PFR WFFK
IN - NUCIIFR fir INPUT TAP!
I(U - MlCMIH Of niJTPUT TAP!
IRIINNI1 - PUN NUMIirR
II|M|||I.,NU) - (AST CIOCK T|«F THAT OUEIJF ID HAD (NO-II TRUCKS
IN f f .
II W - IMK.EK DAYS lir WI(K, l.f. 1,?,3,ETC.
JTR( - IMIGIR NIIMIITR III r Al II TRACTOR
JTRI - Uril.lU NIIMHFH Ill 1 A( II TRAILER
IIRPIL - wi MM Y rntAi (if CUIIFCIION TRUCKS ROUNOTRIPS
.IIRPKi, - WMMY TOTAL Or IRAIIFR TRACTOR R 1 r, S RUUNOTRIPS
K - A (OMRUI VARIADLt, WHf N = 0, RANDOM NUMBER SF H 1 1 S CANNOT BE
nul'IKAIKI IN lULIUWlNG RUMS. IF > POSITIVE INTEGER, THE SERIES
IS Al WAYS THI SAMf * HUNS (.AM RT UIIP1 ICATFO EXACTLY.
K? - (HIINIFK MID TSTM, IIMI SPrNl AT TRANSFFR STATION
K7RK, - A SWITIHINf, VAMIAHll IN USPSl WHICH INDICATES IE MORE
IHAN (M (Vf-NT IS (.(NtKAKI) II Y SUItROOTINF.
Kir«K A SHIKHINI, VARIAHir IN DSPSl WHICH INDICATES IE MORE
THAN (Ifvf (VfNT IS f.ENIHATri) HY SUHKOIlTINF.
KA - A (.IIINn» Kl» (JUT^.I.r. (Jl)T?IK<.l
K") - A VAI'IAIIU SOH'jtRIPT, DAYSIK-i.JI
KAPTS - (APAUTY IN IONS PF R CJAY (IE TRANSFER STATION
KINTHK - (APAMTY OF COILITIIMN TRUCKS
KINIHI - fApAriiY nr TKAIIFKS
KKK - KTfMP - 1
KSIKIS - SIPFSTMO.O
1 - A fl'IINTrH
MA»LU - MAXIMUM tFNCTH Oh TRANSFER STATION UUEUE
NA = AHT A NUMHI H
NARtA - MlfHIR OF ARfcAS 1NTII MHICH TRACT IS DIVIDED
Hf - C(ll 1 KF - I.
HI:H - Niif in H (ir (UFFtRFNT Ruurrs ASSIGNED TO A TRUCK * - 6./COLFRE
NINCII) MJMIIIR |)F ClILIfCTICN TRUCKS IN OOFUE 1.
NN - ANt 1 YIM I )
NIFIIS - NIIMIIFK Or FLATS OR ItHEAKDOWN
NliKIII - NOMHI R OF ROIJTFS INTO WHICH A SUBARFA IS DIVIDED.
M TRL - MIMItR OF IBACTlIRS
N(lk(? - =1(1 » NIIMIII K 01 IKACIOKS.
NTIRK - NOMMIK Ml COLLELIIriN TRUCKS IN MODEL
N( ll<| - MIMHI R (It TRAIL 1 KS
NrVMIl NIIMIIIR OF IIUK.KS WHITH LOGGED
NIVKI? - I, ?, t ovtR 1 HOURS OF OVERTIME
Nt.'VHI 1 - DURINC, WFEK
NI - 1 VI NT NUMI1F R
(IHCf - III! WIAN (IF FHF NdRM/ll DISTMIHuriUN OF TIME SPFNT" Br
IKA1I 1 R-THAI (OR RK.S Al THF FINAL DISPOSAL SIU. IMINIITFSI.
oprf IIPIHAIING Tint or TRACTORS IN MINUTES
(IHHH - AN AI.CUMIJI ATIIK (IF OF 1 ROUTE TIME FOR ALL COLIECTION TRUCKS
IN MINIIII S
(1VPAYI - LAMORIRS OVFRTIME PAY. (DOLLARS PER HOUIU
ovRrn - A suusr.ciPTFD VARIAHIFI OVERTIME FOR COLLECTION TRUCK
IN HOURS. OVRTMINT )
PAYI H« - LAIKiRIKS DAIIY PAY
PFRUN - A SlJIIS(.klPTEt) VARIAHLEt AVERAGE NUMBER OF PERSONS LIVING
IN A HnosFHOtl) UNIT FOR FACH OF THF A NEIGHBORHOOD TYPES
PNHSIG - mr STANDARD DEVIATION OF THE NORMAL DISTRIBUTION OF THE
PIUNDS PI" PI RSON PER DAY OE GENERATED SOLID WASH.
PRHTll - NUPHrK OF BREAKDOWNS PER 1000 MILES OF TRAFFIC FOR
COl 11(1 ION TRUCKS.
U5 - DVFRTIMr PAY PIR HOUR 1 OR TRACTOR DRIVER
06 - DAIIY PAY FOR TRACTOR DRIVERS
01 - YMI'LY LOST TAX RFVFNUF FROM TRANSFER STATION LAND
OB - TIMF IN MINUTES AFTtR /ERO CLOCK TIME WHEN TRACTOR DRIVERS
Rl PORT MIR DUTY.
OS - A RUN CONTROL VAH 1 AfiL F , KHCN * 0. NO OVERTIME IS PAID TO
ClillFCIION TRUCK CREHSt WHEN * 1. OVERTIME IS PAID.
010 - A RUN CONTROL VAKIAHLIi WHEN " O.iALL COLLECTION TRUCKS
A«r CI.NSIL)FH(D TO HAVT TIU SAME TRAFFIC HAUL DISTANCE WHICH IS
FCUAL TO Tilt VALUF flF TRLHAL. WHEN = I. COLLECTION TRUCKS HAVE
nilFLRINI HAUl 01 STANCES. EACH BEING CALCULATED FROM METRIC L
PATHS « RIJADIS.
OIIIAvr - AvfPAGE, OE LENGTH OF COL
LUIKAX - MAXIMUM, TRUCKS WORKDAY
U;I*IN - MINIMUM • IN HOURS
UMSir, - SINI! DEVIATION
(.II^IIII - IIHE OF EVINT •, MIR LAST COLLECTION TRUCK AT QUEUE 1.
LTH - M«l in UUMjr FOR A PAUIICULAR TRUCK.
Ll.llwf - LI/MI ING (IMF FACII IMY FOR TRACTORS
U1, 1 1 IMINT, lliwl - MATRIX OF ijOITTING CLOCK TIME OF TRUCKS, NT, ON
(AY III Till MIK, |DW. IMINOTIS)
(-lir/ - A SUH'.CR IP Tl [) VAIMAHll WHICH IS A VECTOR OF UUITTING
TI"IS M« (OLIiCIION TRUCKS FrjR ENTIRE WEEK. K<, IS ITS COUNTER.
P - AMUR! l/AI ION INTIR1SI RAII FOR TRANSFER STATION AND LAND
KIPIM - 1RAII FK-IHACTI1R l< 1 G T|»F AT FINAL DISPOSAL SITF GENERATED
rfl,M A MiKMAl [II SIR IHIJT ION. IMINIITFSI
M(,UMA« - THI IIPITR IIMII IN MPH FOR T R AC TOR - T R A 1 L E R SPEEDS.
MfUh-IN - nil tllkIR LIMIT IN MPH FHR T R AC TOR - TR A 1 1 F R SPFIOS.
"ILKA - Y IHKRSrCI IN kl(. CESSION FBUATION OE L (If, SPfFOS OF
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
-------
(.
(
(
c
(.
(
c
(.
c
(.
f
<.
(
(.
c
f
C
r.
r
(.
c
(
i
c
(.
r.
C
r.
r.
c
c
r.
r.
t.
c
L
c
c
r.
r.
r
r
r.
r.
c
r.
c
c
c
r
c
c
c
c
c
c
r.
c
c
c
c
c
c
c
c
c
r.
r.
r
r.
c
r.
r.
(.
r.
c
C
c
c
t
c
c
c
c
c
c
c
c
c
c
c
r.
c
t
1 f ft 1 1 Ml - U< M 1 1 U S I,U I' 1 ', 1 ANM .
1' 1 ' >• II M'l II I' II Nt UF INUI I'l Nl;! NT VAK 1 A HI 1 , 01 STANCI i IN
in i,R| S' Ulli lullAllliN III Illl, SIM IDS III IUAII F H- IHAC HlHS DN
i 1 S 1 A N r t .
I' 1 f,M A X Nil Will, HI RAY 1 flAI; IJ! |(|NI, HAUl TRAILER.
R 1 ' VI 1 1 KM, T III' ( H A | 1 ( I' M'l i II M'H
KKfi - Y (Nil I'M M IN RII.KISSION 1 OUA 1 I ON III I Of. SPEEDS OF
1 1 1 1 1 1 < I 1 ( 1 f I 1 1' 1 1 ( K S UN ( ) 1 S I A N f ! .
KK II ( i'l 1 1 II 1 Hit ill I Nlll I'l Mil NT VAH I ABI 1 i 01 SIANCF , IN RFGRFSS ION
II.UAIIIN ill Illl, SI'lll)', III ( 1)1 1 f CT II, N TRUCKS ON DISTANCf.
UK A A 1 1 t 1 Ml 11 Nl S IN HI I, I'l SSI UN I IJUAI ION
I'Klill IIF MIMItl R Of UN 1 1 5 ASSIGNED TO A TKUCK
KHII - Ofl MAIJl DISTANCF • NFIGHBOKHOOO TYPF
I'MXISt Illl IIPI'I R MM! Ill Illl INDI I'f Nlll NT VARIABLE, UISTANCF.
II, H WI'KU ll'l III I, HI SS IUN l;( 1 (,(, SIMM)', IIF LIU 1 f ( T 1 (IN TRUCKS ON
1 1 SI AN( 1 1 ', Al'l'l If AIU I .
KMXIJSII IMI DIMM H 1 IMIT III Illl INOFPINDFNT VARIABLE, DISTANCE,
1 f IK WH 1 1 H ll-l K t (,R| S S 1 UN ()! (Ill, SPF F US (IF 1 H A(, I OR- T R A H F R R 1 F S
IN 1)1', 1 AMI 1 1 ', AP I'l 1C Alll I .
KM, - A I'ANIHIf NUMIIFR
I'UNNU ll'l I'UN NUMIU R
SI (II Ml MIM 01 HIIK'j OilllMION MHFAGF FUR COLLECTION TKUCKS
SMWRM IIIIAI UIMRAMHI, HIIOI", I]F TRANSFER SIATIUN DURING WFFK
SRIf.MI SUM 01 HlfK, MllfA',1 FUR TRACTOR-TRAILER RIGS
r,IAI - SIAIIIS.IN IRAF F IC.WA 1 1 ING.t T C . , OF THAILFRS OR TRACTORS
S 1 A [OS • 0 OIIF IS I MPI Y
si A IDS - i uui i s NU r i MIM Y
STAID". H IKACTOI' IS IDLI
SIAIOS ' ') IHAI 100 IS IN 1KAF-FIC
SFATOS - 10 THAI! HI IS 11)11 AND EMPFY
SIAIDS - 11 TRAHIH IS IN IIIAFFIC
SIATIJS I/ TKAILTM IS 11)11 AM) Fllll
SIAIDS = It TKAIIIR IS I'.FINf, F I 1 L F I)
SIKFPI SUM OF HIFKS IHAI F If. MIFAl.F FOR COLLtCTION TRUCKS
SIKFS! SIARIING TIMF Fill' FIRSI TRUfK OUT IN MORNING » f 1 MF FDR
MINIM RIDS (OFIII ORIAKS [)U« I Nf. DA Y 1 M 1 NU T F S 1
SllfHUI (OIAI f'UMHFR 01 COIIFI.TION ROUIFS IN MODEL
lARIAINI.NIlA) - A UFA TO HHIMI TRUtK NT IS ASSIGNFD ON DAY DNA
IHAI I)S I HI ,NDA 1 - MAUL DISTANCI IOR IRUCK NT CN DAY ONA
IICI - 1 IK! IN HINDUS Al WI'ICH NFXT FVTNT IIAPPFNS
TIflUII.II - AN Arrilflll AI1IK MATRIX SHOWING TOTAl TIMF WHICH
C.UIOI 1 MAS MAD i IRUI.KS WITHIN IT.
TM I Y1M NT ,NDA I - NflVC IIF CIIILIfTION FOR TKUCK NT ON DAY F)NA
IM MDNIM.NDA) - MO. OF UN 1 I S 10 COLLECT FOH TRUCK NT ON DAY ONA
Iff.AGF - WIIDF'I IN IONS BY DAYS
l( T 1 JIRI , JDwl - AN AC.CUMU! AMIR OF OVERTIME HOURS OF I RAC TOR i JTRC ,
f N LAY I,F TMF HF 1 K , JOW.
IF ICDS - IIIIAI COST FDR WFfKS ACTIVITY
IOIFON - IOIAI KINNAdF COLllf.TFD IN WFFK
TK(. - A SUHSCHICTIU VAR1ABLI. TRACTOR NUMBER ASSOCIATED WITH THE
F VI NI NOMI1I R.
IRIS1N - AN A( COMUI ATOR WHICH COUNTS 1HF NUMBER OF COLLECTION
TRUCK KAI TIRFS OR 11 RF AK DOWN S THROUGH THE WEEK
IRIS ^ IMI STANDARD DEVIATION OF THE NORMAL DISIRIBUTION OF
TRAII 1 K-IRACKJR TIMF AT TMF FINAL DISPOSAL SITI.
TRFIIR - AN ACCUMULATOR 01 TRAFFIC TIMF FOR ALL COLLECTION TRUCKS
IN M INIJH S.
TRFIM/ - TIML FOR ONE-WAY COILCCTION TKUCK TRAFFIC TRIP. (MINUTES)
TRIP - A sunsCRiPrru ACLUMUIAIUR WHICH COUNTS NUMBER OF ROUND
TRIPS FIR 1RUCKS • IKACICIKS.
IRKDAY - NUMHFR OF RUUIIS • NUMBER OF COLLECTIONS PER WEEK
TRKIOINTI - WEIGHT CARRIED I1Y IRUCK TO DISPOSAL POINT
ll'l - V\ SUBSCRIPTED VARIABII, TRAILFR NUMBER ASSOCIATED WITH THE
F VI Nl MJMHER.
IHIHAl - DISIAMCF IN Mills FROM TRANSFER STATION TO FINAL DISPOSAL
1RPIIII - NUMBER OF TRIPS HY HHLFCTION TRUCKS DURING WEEK
llll'RK, - NUMBI R OF TRIPS BY 1 R AC TOR- T R A 1 L EFt RIGS DURING WEEK
TKPTM - MINOirs I OR TRAflOR IRAILER ROUND TRIP
IS - 1 M ANSI ! R S 1 A II ON
ISLOSI IIIIAI nisi IN DIIL1ARS FOR TRANSFER STATION •
ISMR IMHIINI IIF MMt IHOCKS SPEND AI TRANSFER STATION
ISIHI'A - DAILY I'A < FOR IRANSFFR STATION lAFtOKER (DOLLARS)
ISIM - HINDUS WHICH (.01 1 Ff. 1 1 ON IRUCK IS Af IS
IX - X (IIIRIJINAIF OF TRANSFFR STATION
1Y - Y (I'ORMNAK OF TRANSFIK STAIION
DNAfRI - f.UMBI R in HOUSING UNI IS PER NE I AC.RF
UIIIIY - MUNIIil Y UMI 1 IYI WAI! H.FIECIRICI TY.F 1C. I COST OF TRANSFER
S I AT II.N.
VFIMAX - UI'PIR LIMIT OF COLLICTICN IRUCK TRAFFIC SPEF.O. (MPH)
VllMI'l - VdHIR LIMIT OF CM 1 ft T. I ON IKULK TKUFFIC SPftD. (MPHI
VI I Ml)» - Mt AN OF NORMAL DISIKIBUTION OF LOG SPEFDS FOR OISIANCFS
GRI ATFR IHAN RMXCSR.
VFLMUT - MFAN UF NORMAL DISIRIBUTION OF LOG SPEEDS FOR DISTANCES
GHfATFR THAN RMXDST.
VFLSf.R - STANDARD ERROR OF ESTIMATE OF REGRESSION OF LOG SPEEDS
CF TRAILER-TRACTOR ON DISTANCE.
VF-LSIT - STANDARD ERROR OF ISTIMATE OF REGRESSION OF LOG SPEEDS
CF TRUCK UN DISTANCE.
WATt(NT) - WEIGHT IN POUNDS TO BE COLLECTED IN DAY BY TRUCK NT
W/.1FZ - NF1 WEIGHT PAY IOAD OF COLLECTION TRUCKS
WT - AN ACCUMULATOR OF WFIGMT COLLECTED EACH DAY. (POUNDS)
XM - ANCKOI (I), A VARIABLF USED TO CONSERVE SPACF
XI AY - MIMBI R OF COLLECTION TRUCKS IN USE FOR FIRST COLLECTION
HI I'll II IM! k.((K, TMIHI MAY fl F FFWFR ON IATFR ROOIES.
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
MAIN
-------
I,KMI I
S I H I)' I I III I
IF "UN AM) I) I Ml N'. I
I VI AU , Mil' AMIKII/AIIIIN III I "ANSI I H S I A I | UN
lUDlI'MINI (AI'IIAI INVISTMINT.
I U" MSI I'Rtir ( S'. INI, RIIUI I Nl S
I ( fMIlN I!1. Ill,, If A( UK , I < HI I f , II I I If, K , ICIIRt , IUUMM2,II)UMM4,IFRST2
I I KM UN I I II S I 't , |( II SI tl, I IIVWHI), I I I Mt 1, I I |MI 2, I IYPF 2, JBUI,, |l"MFf K
( 11C M IJN MA/I K| ,MAXlNI,MAXl,llYPFl
I) I f I f|S I IN I ( IIH I ( 1 I)'|(J ) t I (Mil ( Ml )
I (.11 I V At f Nl ( I I f l)Pf ,1 f;H I )
rilfflJN ANIJ IIIMIMMtJN H>H SIMUIAMUN
< I KMMN /III1/ AT.AIHt.AHAIDS.AM t Y I' , ANUHUN , ANORU I , A SNUP T ,
1 A A', SUN, AS SS UN, A', SUNK,AX1,AX2,AY1>AY2,B,C(, LtCLKTM,
> n| FHI ' , ( I II MM, (.(I I CLK.r.OI IMZ.C, [jMPAP.CIJNA.f UNH,
i UN'. ,i ijNh.riiNi ,( UNF ,rasf m ,t, IIHAC K.CIISI ND,
4 «[WISiCfHS/,(. SMKM. ,rSTMH,tIS.I)»YSil)ILOFMiOMTAVEi
s )M7M/ix,i;Mr«iN, >vrs ir, ,1x11 nil ,ixn a tr,,uR(jVMAXlKbVMINtKIGKA
(CKKdN /HO/ HII, KR, Mil, MAX, R IC.VI I , RK A , RK A A , RKtl , RKBH , RKCC ,
1 Rl)»l)lc, ,HMXnSH,K"XOSI ,RNU,KIINNO, SCUL ML . SMWRKT ,
? SRir.MI , SI AT, MM I SI .StRFML.SUMHUT.MJMTRK,
? !ARfA,ll|(m
L
2
HISr42ll6),"ISr.4)ll6l HISC44(16),HIStDlll6>,
H 1^ rill I U) .HI Sill 2 I 16) HISTU3I 1M.H1 STU4I Ifcl ,
MPTM(fcO) tOVRTMISOl PFRUNI4) .QOI50I ,
OUITMLI60I.UUI?! (00) R(IAI)ISI25),STATI90I
TIMFI60) ,rilNAI,M6l TOTMTI50) .TRCI60I ,TRIPI90I
THKLOI50I ,TRII6DI TSTMI 1000) .WAIF 1501 ,
IIAYSI2.3), ITIMII2.12), OIJI T TM I 50, 6 I , RKAAI4.2),
RKnill4,2l, KKCC(4,2),TARFAI50,3),THALr)S(50,3l,
IIMEQI2.12I, INF IYPI50,3), TNOHUN(50«3I
• STARI flF SIMUIATKIN
MAIN
MAIN
MAIN
OOIOMAIN
0020MAIN
OniOMAIN
00()MAIN
00 /DMA IN
OOHOMA IN
OO'IOMAIN
01 DOMAIN
01 10MAIN
OI20MAIN
01 30MAIN
OHOMAIN
0150MAIN
Ol'iOMAlN
01 DOMAIN
01HOHAIN
01'*OMAIN
0200MAIN
0210MAIN
0220MAIN
0230MAIN
0?<.OMAIN
0250MAIN
02'.OMAIN
0? ?OMAf N
02HOMAIN
02'IOMAIN
0300MAIN
0310MAIN
0 )?OMA IN
OHOMA1N
0340MAIN
0350MAIN
0360MAIN
0370MAIN
OiHOMAIN
0390MAIN
OAOOMAIN
0410MAIN
0<.20MAIN
0430MAIN
0<>50MAIN
O^hOMBIN
0470MAIN
0,
1 I nil I 1 , I'* , INLRMI , ICHj. I RUNNtl, I I I Ml , JI)W, JIHC ,
0010 BLK
00?0 BLK
0030 BLK
OO'iO BIK
0050 BLK
OOftO BLK
0070 BIK
OOHO BLK
0090 BLK
0100 BLK
0110 BIK
01^0 HLK
0130 BLK
0140 BLK
0150 BLK
0160 BLK
0170 BLK
0180 BLK
0190 BLK
0200 BLK
0210 BLK
0220 flLK
0230 BLK
0240 BLK
0250 BLK
02f>0 BLK
-------
31
? JTRl, IH'HC.I , 1 IKI'K(,,K ,KJ,K'. ,K5,KAPTi,K INTKK,
\ KINIHl,KSTMfS,Ktl'DPtHAXLO.NA,NA«CA,NC,NnA,
VRTM,I'AYLI)M,PERUN,PNOMU,PNOSIG,
1 PRBFI I, CO, 01,02, U3, 04, 05, 06, Of. 08. 09, 010,
H yll.OMAX.QO.UIJIAVF.BUIMAX.UUlMIN.OUISIG.
1 gulTMC,t;UlTTM, , ANOHUNI 25 1 , ANORUT ( 25 1 t
1 ASNUPt (?•>! ,AASSUN(25I ,AX1 (25) ,AXZ<25) i
2 AYK^SI ,AY2(25), HI 10) ,CCL(6) ,C.GLMLK(4) >
) U)RAr.K(4) .CTSI6I ,FVFNT(60I ,H I St 1 2 1 16 I .
4 HISC 11(16). HISC 14(16), HISC22(16),M ISC 231161,
5 HIS C 74 (16 I .HISC 321 16 1 ,H1 SC 33(16), HISC 34( 16) ,
6 >mc<,2ii6>, HISC 41U6I, HI sC44(i6i,HisrDUi6i,
7 HISKJ 1(161. HISMJ 2(161, HISTLmiM.HISTU* (161.
H (1PTMI60I .OVRTMI50I ,PtRIJN(4) ,00150) .
1 (jUI IMC (60), UIJTPI 3001. RH ADI 5(25), STAT 190)
UIPFMSKiN T1fl(60l ,TfJNA(,((6I ,TOTWT(50I ,TRCI60I ,IRIP(90I ,
1 TRKLDI50) .TKLI60) , T STM ( 1000 ) , HATE 1 50 I .
2 OAYSI?,3), ITIMII2,12). UU I T TM ( 50, 6 1 , RKAAI4.2I,
1 RKBH(4t2l. RKCCC.,2),FARCA(iO, 3), FHALDS ( 50. 3 > ,
<• TIMiU(2,121, INI TYPI50.3) , FNOHUNI 50 . 3 I
OATA CUfPAP.CONA.CfJM) /O.O, .<,0 /
OAFA (IHCFf,()RI)PAY,OROVKF / 0.1, 19.80, 3.67 /
DATA FlUTM.FX.ry / A5., -39600. , 39000. /
OAtA IN. KHI.KINTRK.KINTRL / '5,6,20,75 /
OAFA NARf A.ONCl.DVPAYL / 13, H., 3. 37 /
CATA PAYLIIR.PNnHU.PNDSIR / 1 8. , 1 . 95 , 0. 09 /
OAFA PRHFlI.OS.Qft / 0.001,3.75,20. /
DATA CH.Cfl.R / 0.0, 60. ,0.10 /
DAFA RGVf AX.RGVMIN.RIGKA / 0. /
DMA VFlKUR.VFLMUT.VfiLMIN / 1.605,1.605,10. /
DATA VELSGR.VFLSGT.WATEJ / 0.1366,0.1366,8700. /
OATA YRS / 30. /
OATA ANf HUN/ 5711., 1099. ,6124., 2079., 11 186., 9659., 7299. ,1887..
1 5906., 10519. ,6731. ,2317., 3937. ,12«0./
OATA AX1/ 53100., 5'. 20 0. , 56400. , 62100. , 63200. , 59500. , 29300. . 82600.
1 81500., fl3000.,U600., 66600., 62100., 12*0. /
OATA AX2/ 66000. , 54?00. , 564 00 ., 66000. , 6 3200. , 66000. , 29300. . 82600.
1 B1500.,83COO.,(.6',00.,66nnO.,66'iOO.,12»0./
DATA AY1/ J<.600.,41flOO. , <,5600. , 42200. . 38500. . 32900. , *2900. . 38700.
1 )5500. ,31 100., 28600., 2B300.. 28000. ,12«0./
OATA AY?/ )9 000. ,M BOO., 45600. ,39000., 38 500. ,39000. ,*2900. , 38700.
1 35 500. .31100. ,10600. .28)00. .30600., 12*0. /
DATA COIMLK/ 550. . 750. .075. . 1000. /
DATA DAYS / 6HM(]NTHU.AM MHF ,6HTUEFR1,6H TTS ,6HWEOSAT,6H
DATA MIS(1? / 5., 1000. ,6000. ,22. ,36. .22. ,10. ,10., 8«0. /
DATA HISt.ll / 5., 1000. ,6000., 10. ,22., 16. ,22. ,10., 8»0.. /
DATA HIS(.l / 8..20CO., 10000. , 8. , 23. , ?<,. , 2 1 . , 1 2 . , 6. , *. , 2. , 5«0. /
DATA HISC43 / 8., 3000., 11000. ,8. ,23. ,2*. ,21. ,12. ,6.,*. ,2. ,5*0. /
DATA HISC',', / 8., 3000., 11000. ,8. ,23. ,24. ,21. ,12. ,6., 4. ,2., 5«0. /
DATA H1STT1 / 10. , 2. , 12. ,H., 10. ,26. ,20. ,8. ,4. ,4. ,12. ,6. ,2. ,3*0. /
DATA HISTU1 / 4. ,2. ,10. , 1 4. , 20. , 46. , ?0. ,9«0. /
DATA HIS1U2 / 5., 10. . 20. . 5*20. ,8«0. /
DATA HISTU3 / 4. ,20. ,40. ,42. , 2»2 3. , 1 2. . 9»0. /
DATA H1STU4 / 4 . , 40 . , 80. , 50 . , 4 1 . , 5 . , 4. , 9«0. /
OATA PFK1IN / 2.7,2.9,3.1,3.4 /
DATA ROAOIS / 0., 11900., 124CO. ,0., 2600. ,0. ,8300. ,12500. ,8900..
1 16100. ,10200., 13100., 102 00., 12»0./
OATA RKAA / 1155. ,1393., 1264., 1129., 1224. ,1878. ,1703. ,1555. /
OATA RKl'R / -39. 3, -53.0, -49. 1, -41. 6, -16. 8, -77. 9, -68. 3. -64.4 /
DATA RKfC / .759 ,.9f6 ,1.015, .874 ,.715 ,1.601,1.447,1.429 /
FNC
02(0
0?HO
0290
0300
0310
0320
0330
0340
0350
0360
0370
0380
0390
0400
0410
0420
0430
0440
0450
0460
0470
0480
0490
0500
0510
0520
0530
0540
0550
0560
0570
0580
0590
0600
0620
0630
0640
0650
0660
0670
0680
0690
070(1
0710
0720
0730
0740
0750
0760
0770
0780
0 790
0800
OR10
,0820
0830
,0840
0850
.0860
0870
,0680
0890
0900
09 10
/0920
0930
0940
0950
0960
0970
0980
0990
1000
i n i n
1 1' i u
1020
1030
1040
1050
1060
1070
1080
1090
1100
1110
1120
1130
1140
1150
1160
1170
BLK
BLK
BIK
HLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
8LK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
RLK
niK
BLK
BLK
SLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
BLK
-------
32
C B M K •
SIJMMIJIJI INF I! 1NURM ( X t Y t KHIJ I
<- .S'( I . < SURTI l.-RH(]«XHOI I
A-SLHT(CI
ll'SK.NI SCKTI l.-CI ,Mhll)
S-6.2H J?"KNNR< 0)
T-SURTI-2.»Ainr, (RNNRIOMI
II-MUNI s>
V' T«(.()SI S I
X-A»U«B«V
v-n»u+A«v
RT TURN
0010 BNO
0020 BNG
0010 BNO
00*0 BNO
0050 BNO
0060 BNf)
0070 BNO
OOHO BNO
0090 BNO
0100 BNO
0110 BNO
0120 BNO
01 JO BNO
«IBf1C CAIIS*
SURROUTINF CAUSf(ITVPF,IDND,ItIME)
COMMON UNO OlMfNSlON FflH LIST PROCESSING ROUTINES
CTMMUN I BUG, IfALOR, [CHECK, (CLOCK, I CORE, IF)UM,M2, IOUMM.*, IFRST2
COMMIIN lFHSr<,,IFRST8.lOVRHO,mMri,[TIMF2,lTYPF2,J6UG,JCHFCK
trim IN MAXCRE,MAXINT,MAXT,ITYPF1
HIMFNSION ICORfl lOOOli CORFI50I
CCltlVALFNCI I I CORF. CORF I
COMMON ANn DIMENSION FOR SIMULATION
COMMON /BO/ A9,ACRF,AHAIOS,ANFTYP.ANOHUN,ANORUT.ASNUPT,
1 AASf,UN,AS5SUN,ASSIJNK,AXl,AX?.Ayl,AY?,BiCCLiCLKTM.
? CIlLFRF.CnLHR.Cril MLK , COL If I, COUP AP , COMA, CONB ,
3 tONC,CnND,C(lNF,CDNF,CDSCOL.CORACR,CUSLND,
* CREHrS,CRUSZ,CSHRTC,CSTHR,CTS.DAYS,OFLDEP.OMTAVE,
5 I)MlMAX,nMTMlN,()HrSIG,001.Cl)L,nOLRIG,OOLTON.
6 UOlTS,OR[JPAY,OHI)VRT,nSIC,DW.FVENT,F INDAY,
7 FlATNn,FLTLTM,FX.FY,HlSC12,HISCU,HISCl<.,
fl HISC??,HrSC2),HISC2'.,HISC12.HISC33,HISCTt,
1 HI SCHI SC«RlRGVMAX>RGVHINtRIGKA
CTPMON /FID/ Rlr,KB,R 1 GMAX, R I GVEL , RKA.RKAAt RKB , RKBB ,RKCCt
1 ROAUI S.RMXI)S»,RMXnST,RNO,RUNNO,SCOLML,SMWRKT,
2 SR1GML,STAT,STMFST,STRFML,SUMRUT,SUMTRK,
1 TAReA.THALOS,T[ME,TIMEOiTNETYP,TNOHUN.
« TCNAGE,nJTCOS,TUTU)N,TUTWT,TRC,TRCSIN,TRES,
5 TRFHR.TRFMLirRFTMZ.TRIP.TRKDAY.TRKLn.TRl,
6 TRLHAl,TRPCOL,TRPRIG,TRPTM,TSCOSr,TSHR,
7 TSLBPA.TSTM.TX.TYtUNACREiUTILTYtVELMAX,
H VFLMIN,VELMUR,VELMUT,VELSGR,VELSGT,WATE,
9 HATEZ,HT,XOAY.YRS
OICENSIUN AHALDSI25) ,ANCTYPI 25 I,ANOHUN(25 I,ANORUTI 25 I,
1 ASNUPTC25I ,AASSUN(25),AXH25) .AX2I25I ,
2 AYK25I ,AY2(25I, B ( 10 I ,CCL ( 6 I .COLHLKI << I ,
3 CORACRd) ,CIS(ft) ,FVENT(60» .HISC12I16I,
« HISC13(16),HISCl'.(16).HISC22ll6),H[SC23(16li
5 HlSC?M161.HlSC12(16),HlSC33tl6)lHlSC)4ll6)i
6 HISC0) ,TflNAGF(6) ,TOTWT(50) ,TRC(60) ,TRIP(90I
1 IKKLDCiO) .TRLI60) , T STMI 10001 , HATE I 501 t
2 OAYSI2.3I, ITIMU2,12), OUI TTM ( 50, 6 ) , RKAA(*,2I,
3 RKBBC.,2), KKCCU,2I,TAREA(50,3).THALDS(50,3>,
« TIMFUI2,!?), TNFTYPI50.3). TNOHUNI50.3)
CAU H;ri
-------
33
I (Jl I V Al I fM I ( I M'M ( , I (
IN rtNl I; | PI fjs | (m f [
SIMUATION
( C fl*ll'l /Id / A9, Af.KI ,AHAI IIS, ANF T Y P , ANOHUN , ANOR U T i ASNUPT,
I AA', SUN,ASSSI|N,ASSUNK,AXl,AX2,AYl,AY2.B,CCl,CLKTM,
2 (l!lFIM,(llltll<,COlMIK,fOlIM/,COMPAP,CONA,CIJNH,
1 f IM. ,f (INU,< ONF .UJNF ,COSUlL,C(jRACR,COSlNI),
4 [RiHis.rKos/.fSHRTc , cst HR, cis, DAYS, IJFLOFP.UMTAVE,
5 ()M!MAX,OMIMIN,I1M t S IG , UOLCOL .001 R IG ,<>OL ION,
6 OOL !S,I)K[)l'AY,l)RUVRr,l)SLC.DH,FVENT,FINOAY,
/ FIATNr),FLUIM,FX,FY,HtSC12.HISC13,HlSC14,
I! HIS(.22,HISC2 ),HISC2<,,HISC32,HI SC33.HISC34,
9 HI Sf.42.HI SC4 3,H I SC44
( (If MON /I'll/ HI SIOl ,HI STUl.HI STU2.HI SIU3,H| STUA,
I Kflim,IN.INCKfr,lnu,IRUNNO,lrlKL,jnw,JTRC,
/ JIKI , IIRPCI , JTRPKG,K,K2,K4,K5,KAPTS.KINTRK,
) KINll'l ,KSTMI S.KIMnP.MAXLU.NA.NARFA.NC.NDA,
4 NI)R,NN,NUKUI,Nliri T S , NO TRC , NO TRC 2 , NO TRK ,
5 Norm ,NOVKT 1,NIIVHT2,NOVRT3,NT,ONCE,OPTM,
6 lllll| tAY2!2il, HI 101 ,CCL (6) .COLMLKI*) ,
1 UiRArnc.) ,(.T',(6I .FVFNTIiSO) .HISC12U6),
« Hl'>(. 1 )l 16) ,HISf, 1'. I 16) .FUSC/21 16) .HISC23I 16) ,
"> HI«, (. f,( It, } ,HI V. IS I 16) ,HI SC 131 16) ,111 SC i HISf'.;il6),HISC'.lll6l,HISC'i'ill6),HlsrDl(16),
7 HIS IUlll6l,HISTU^(16),HISTU3(16),HISrU(2>3)t 1IIMLI2.12), OU1 T TM( 50,6 ) . RKAA(4i2)t
1 RKRHC.,?), kKCCI A, 21 .TARFAI50, 3) , THALOS(50,3) .
<, I[MFU(2,L2I> TNFTYP(50,1I , TNdHUN I 50, 3 )
132 NFTYP - fNC TYPI NI ,NOR I » 0.5
IF I TRIIMNT ) .NF.O. ) GO Tf) 200
100 TRIPINI I = 1.
RNH = RNNRIOI • 100.
GC TO ( ?0?,20<.,?06,20B) , NFTYP
202 CALL HISItHlSIUl.RNn.Y)
GC TO 210
204 CALL HISTIHISTU2.RND.YI
GO TO 210
206 CALL HISHHISTln.RNO.Y)
(,o 10 ?in
20B CALL HI SI (HtSTU'i.RND, Y)
210 UNACRF <• V
ACRE = INCHUNINT.NDRI • COR ACR I NE TYP ) / UNACRE
CALI RAN1.C Ml PNDMI),PN[)SlG,PNOPrR I
HATFINI) - P(RONINFTYP) • PNOPFR • OSLC • FNOHUNI NT ,NDR )
WT WT t WATF INI I
SCOLPL • SCOLML « (ACRf • COI MLK I Nt T YP ) / 5280.)
?00 RNU -- RNNH(O) • 100.
N 3N ' I) SI C - U
(.1) 1012 71 ,77?, 273, 2 T, I ,M \1V
271 ',ri 101 ^H 1 ,^H/,?H3 I ,N 3N
27? C.(; Till ?H'.,2HC.,?HM ,N3N
/ 7 3 (,n IIH2H/t2BH,?H')t ,N1N
2M l,n IO(2'*0,?'U,217) ,N)N
?B1 CALL HIST (HI SC12.RND, Y)
t.r TO 2
-------
1,1 III /•)',
29t) f Al 1 ll| ', 1 | HlSf 42,KNTj , Y I
M II 2')->
291 ( Al HI <,| (HI SC 4 l.SNH, Y|
f.f II ?•>',
29? fAl HI', I 1 HI M 44.RNO, Y 1
295 ffil AT . y
Til • IMwT INT ) » HATFZ
II 1 ! 1 T.I T.WATFINT ) ) On Tfl 7Cf)
r,t in 400
700 TTT? * TIT < 1000.
11 1 III2.I F .MAIC INT) > GO TO MO
(.1 Ml '.CO
710 ii iwMNii • IOIWTINTI » WATI;
1 R K 1 I) 1 N 1 I « W A T t /
f.f III 7^0
400 1KKIIJIMI • WATI(NT) - IOTWTINTI
IXIM I - 1.
720 1 I/I M INT 1 « 5.
rntlM' • Itl'KILHNT) • 60.1 / COLRAT
T IM INI I • 1 IMMNI 1 * COLTM/
C (II HK - ( fll HR • rill TM/
Itf IIJHN
f MJ
MBFTC CR>A«
C
C
C
C
C
C
r.
C
5(JHHI«;IINI fRFATF ( NOH, 1 fJNO 1
f.OMMflN AND DIMhNSlON FOR IIST PROCESSING ROUTINES
C( MM.ON 1 IIIJI, , 1 C AL OR, ICMFCK, 1 CLOCK, 1CORE , IOUMM2 , 1 DUMM4 , 1 FRST2
r Of Ml IN IFR', 14, IFRSTfl, IIJVRHI) , I T I MF 1 , 1 T 1 MF 2 , I T YPF2 , JBUG , JCHE CK
CCMMON MAXCKt,MAXINT,MAXI,IIYPEl
DIPFNSK.'N ICORHIOOO), CUKFI50)
F CUlVAl INff I ICORF ,CCRE 1
COMMON AND DIMENSION FOR SIMULATION
COMMON /nn/ A9.ACRF , AHAI US, ANEI YP.ANOHUN, ANORLJI , ASNUPT ,
1 AASSUN,ASSSIIN.ASSIINK,AX1,AX2,AYI,AY2,R,CCL,CLKTM,
2 CdlFRE.COLHR.Cni ML K , COL I MZ ,COMPAP,CUNA ,CONB ,
3 CflNC ,r.ON(),CONF ,CONF,COSCOl .CORACR ,COSl NO,
4 CRIWTS,CRUS?,CSHRTC,CSTHR,CTS.DAYS,OELr>FP,OMTAVE,
5 [)MTMAX,()HTMIN,f)M 1 S 1 G , nOLCOL , DDL R I G , DOL T ON,
6 OOLTS,OaDPAY,l)ROVHT,DSLC,OW,EVENT,FlNOAY,
7 FLATNO,FLTLTM,FX,FY,HISC 12,HISC13,HISC14,
8 HIS(.22,HISC2),HISC24,HISC32,HISC33,H|SC34,
9 HISr.',?,Hl SC43.HISC44
CnMMUN /HP/ HI bTDI ,HI STU1 ,HI STIJ2.HI STU3,HISTU4,
1 1CIII 1 R, IN, I N(. RMT , IQU, 1 RIINNO, I T IMl , JDW, JTRC,
2 JTRl , JTRPCL , JTRPRG,K,K2,K4,K5,KAPTS,KINTRK,
3 KINTRL,KSIMFS,KTMUP,MAXLO,NA,NAREA,NC,NDA,
4 NRR.NN.NURU I.NOEL T S , NO TRC .NOTRC2 , NO T RK ,
5 NOTKI ,NOVRT 1 ,NOVR T 2 ,NHVR T 3 ,NT ,ONCE,C)PTM,
6 ORHH,IIVPAYL,OVRTM,PAYLBR,PERUN,PNnM.U,PNDSIG,
7 PR HFLT,00, 01, Q2,Q3, 04,05,06, 07, Q8,(J9,ylO,
B C11,QMAX,QO,OUIAVF,QUIMAX,OUIM.IN,OUISIG,
9 OUMMC ,aUlTIM,OUI2,R,RGVMAX,RGVMIN,RIGKA
COMMON /CD/ RI&KB.R 1 GM AX , R I GVF 1 ,RKA,RKAA, RKB , RKBH , RKCC ,
1 ROAUI ', .HMXDSR.RMXDST.RNU.RUNNO.SCOLML.SHWRKT,
? SRIGML , STAT,SIMFSI,STRFML,SUMRUT , SUM IRK,
3 TAREA,THALDS,I|MF,T 1 MEO, TNE T YP, INOHUN,
4 TONAGr,TOICOS,IIJITON,TOIWI,TRC,TRCSIN,TRES,
5 TRFHC.TRFML.IR.CTMZ.TRIP.TRKDAY.TRKLD.TRL,
» IRLHAL.TRPC OL,TRPRIC,TRPTM,TSCOST,TSHR,
7 TSLH('A,TSIM,1X,IY,UNACRF,UTILIY,VELMAX,
B VFLMIN,VELMUR,VHMUT,VELSGR,VELSG T.KATE,
9 WAH ; ,WT , XOAY.YHS
DIMENSION AHALI)SI2'i),ANHYPI25l .ANOHUNI25I ,ANORUT(25),
1 ASNUPT ( ?5I .AASSUNI25I ,AX1 (25) .AX2I25) ,
f AYM25) .AY2I25I, R( 10).Ctl<6).CL)lMLK(*) ,
3 COMACRI4) ,CISI6I ,EVENT(60I ,HISC12(16),
4 HISC13(l6),HISr. 14(161, HI SC22I16I.H ISC 23(16),
5 HISC 241 161 fHISC )2(I6I, HI SC 33(161, HI SC34I16),
6 Hi SC42I 161 . HISC 4)1161, HISC44(16l,HISIUl(l6l,
7 HI SI 111 ( 16) ,111 STU^I 16 1 ,HI STIJ3I 161 , HI SIIK.I 16) .
H UP 1C (60 I ,OVKTMC)0) ,PfRUN(4) ,00(501 ,
9 LIM IMC 1601 ,011121 )OOI ,ROADISI25I,SIAT(90)
UIMINS1I1N IIMII60I ,T(INA(,II6I ,10TWI(50) ,IRC(60) ,IR[P(
-------
35
1(1 1 1 1 1 1 1
1(1 1
102
104
Al 1
1 II
1
A
(
A
IOS If
1 1
1
Ml
t
HI
" '. 1 ', 1
1' 1 M 1 ',
K",
1' ', 1 H I
K 1 M| ',
( 1 1 M
till',
1 / 1 - 1
IM2
Mil
'100
III!
i ') 1
1 1 II
( f IK!
, |n2.
f*i :, 4 ,
.'100,
<< M , M ,
1 IjtJMM
N(J>4 ,
I 2) • 1
HI 1
II K',
104
If K',
4
4, 1 Fk
14 1
1 8 1
ST4 1
300 IFIMIM-2) 600,101,610
10 I IF I I I I'1, t / | 102 , 102, 103
303 (.All "I Ml ST I | DNII, ?, IF RM2)
(,( 1(1 11)4
* 0 2 I M I I '< '» I 4 1 i 0 S , J 0 S , ) 0 6
306 (Ml HI Ml ', I ( [DNII, 4, IF RSI4 I
IK KM II Ml« 1 I' I DIIMM2
( Al L Ml I M I II Nljt 2, 2, IFKSI2)
(,f 1!) 3C4
SOS IF ( I M'S I H I'lOO ,'(00,30,
307 f Al 1 Kl Ml ', I I IDNIJ H,IFRSIHI
I ( ( K I I I DNII » 3 I ^ I (J MM 2
(All Ml I ', I ( ICNn 2, ?, IF RST2 I
II I KF I I I M:>'I I" I I) MM4
(All Ml I ', I ( ICNIJ 4,4, IFRf,T4 I
304 If CHI I 1 1 K OKI II • 1
70(1 IK KM 4 1 K IIHI I 41 »NIJM
I - 111NI! * t,\\M - 1
i:(l 701 I - IDNII, )
701 If CKF I I t 1 I -- 1
BOO HI TUKN
KM I llf'MAH ///1 X, 1 2HAI KIIICK * ,lfl,13HANO JCHFCK
Xl'jHA IUIKK 111 ', l/r , I B, 1 211 WAS ("RIAIFD/IX,
Y4IHIIMY IIIIK.KS llf SI7F 2,4, (IK B AHI AtlOMtU)
ftOO WKIII (1(11,601) If.l DCK, K HK.K.NUM
If HI CK »2
f, Al L PAN K
901 f C'HMAI I III- 12HAI ir.lOCK -- ,|H,13HANFJ JCMECK - i
X2')F< DYNAMIC SIUI'AGf HAS fX(.llllFU)
')0(J WHIIf (Kill,'1011 ICLdCK, JCHEI K
I C I I C K > 1
r,r ID HOO
EM!
,IS/1X,
I8/
o^ ''i ( xf
OMIO < KF
O'>'(0 r«f
O7oo c«r
0710 CRF
07?0 CHf
0 M 0 C K F
0740 CRF
07->0 CRF
07(»0 CRF
0770 CDF
07HO CRF
07'JO CRF
OflOO CRF
OHIO CRF
OH70 Ckf
OS)0 CRF
0840 CRT
ORSO (RF
OB60 CKF
OH70 CRF
OHflO CRF
OH'(0 CHF
0400 CRF
0910 CRF
O'l/O CRF
O'(i0 CKF
O'(40 r.Rt
o'CjO CRT
0960 CPF
()'I70 CKF
09HO CRE
O'CIO CRF
1000 CRF
1010 CRE
10^0 CRF
1030 CRF
1040 CRF
10^0 CRE
1060 CRF
lO'O CKF
10HO CRE
SIJHKIIIir INF RAFMAK
COMMON AND DIMENSION FOR LIST PROCESSING ROUTINES
CTJMMIIN lnur,, ICALOR, ICHFCK, 1C KICK , I CUR E , I OUMM2 , IIJUMM4 , I ERST2
COMMON irRST4,lFRSTB,IOVRIIO,ITIMFl,ITIME2,ITYPE2,JBUG,JCHECK
CflMMIlN MAX CRF ,MAX INT ,MAXI, ITYPE I
DIMINSICN ICORIllOOO), CORMSO)
I CIIIVAI f NCM ICIJRE ,COKF I
(OMMIIN AND DIMINSION FOR SIMULATION
C(;MM(1N /HD/ A"), ACRF ,AHAl OS , ANE T Y P , ANUHUN , ANURUT .ASNUPT,
1 AAiSUN,ASSSUN,ASSUNK,AXl,AX?,AYl,AY2,H,CCL,CLKTM,
i COI I KF ,C()LHR,C(H MIK ,COL TM,;. ,C[)MPAP,CONA,CONB,
3 r.oNt ,C(iNn?cuNr,(iiNF.cosf OL.CORACR.COSLNO.
4 C.RI Wl S,f,RUS/,CSHKTC,CSIHK,CTS,l)AYS,!)ri()fP,DMTAVE,
•> (If I MA X, DM1 M IN, DM IS I G, Dill COl , DfX K I f., DfIL TON ,
ft 1)01 I ', ,l)RDPAY,l)KIIVRt ,OSI C.DW.FVFNT ,F [NDAY,
7 Fl ATNII.FL H IM,F X , E V , H I SC 1 ? , HI SCH.H1 SC14,
H III ', I. ? 2, H I SC 2 ), III V. 14 , H I SC 3 2 , H I SC 3 3 , Fll SC 34 ,
9 HISC4?,HISf43,HISC44
KIMMIIN /I)D/ MISID1,H I Still ,HI SMI?,HI SIU3,HI SIU4,
1 I rill TR, IN, INCRM! , IOU, IKUNNU.I TIML.JOW, JTRC,
? JIKI .JIUPCI , JIUI'fG,K,K?,K41K5,KAPTS,KlNIKK,
3 KINIKl,KSIMFS,K!MOI',M«XH),NA,NAREA,NC,NOA,
4 NIIH,NN,N[)Htn,Nliri I S , NO I HC , NOTRC 1 , NO I RK ,
% NCIRL ,N()VKI 1 ,NI)VHIP,NOVRT 1, NT, ONCE ,(JPTM,
h OHHR,nv('AYL,f)VKIM,PAYLBR,PfRim,PNRHu,PNDSIG,
7 PRIiFI 1,00,01 ,U<>,U3,U4,Qr>,06,07,US,09,010,
H 01l,OMAX,OU,OUIAVF,OUIMAX,(JUIMIN,QUISIG,
9 OUIIMC. ,OUITIM,OUT2,K,RGVMAX,Hr,VMIN,RIGKA
CCfMDN /I'D/ RIGKH.K IGMAX.R I (, VF L , RK A , RKA A , KKB , RKBB , RKCC ,
1 KOADIS.RHxnSH,RMXOST,RND,KUNNO,SCOLML.SMWRKT,
2 SR|GML,STAT,SIMFST,STRFMl,SUMRUt,SUMTRK,
1 IARFA,VHALnS,FIMr,IIMEa.TNHYP,INOHUN,
4 T()NAr,E,TOTCI.S,Tt!ITON,TOTWT,TRC,TRCSIN,TRES,
•> TRFHK.THFML, FRF IMZ, TRIP, IRKRAY.TRKLU.TRl,
h TRLHALiTRPCOl,TRPRIG,TRPTM(TSCIJSTitSMR,
7 TSLHPA,TSTM,TX,TY,UNACRE,UTILTY,VEl.MAX,
H VCLMIN,UELMUK,VILMLT,VF;LSGR,VELSGT,WATE,
q WATt?,HT,KOAY.YKS
I) I PENSION AHALDS(25),ANEIYPI25),ANOHUN(25),ANORUT(25),
1 ASNUPI(251,AASSUNI?5I,AX1I 251 ,AX2(25I ,
2 AYH^bl ,AY2l?">), Bl 101 ,CCL<6) .CULMLKI4I ,
3 CORACRI4I .CISI6I .rvFUTISOl .HISC12I16I,
4 HlSf 131 1H ,HISC 141 161 ,HI •)( ?2I 161 ,HI SC? )l 161 ,
0010DATM
0020DATH
0030DATM
0040DATM
OOiODATM
00600ATM
00 70DATM
00800ATM
0090DATM
0100IIATM
0110DATM
0120UATM
01 30FIATM
0140DATM
0150DATM
01600ATM
01 700ATM
01HODATM
OI900ATM
0200DATM
02IODATM
0220UATM
02300ATM
0740DATH
0?60DATM
02 700MM
02HOOATM
0290UATM
0300U4TM
03100ATM
0320DATM
0330UAIM
0340DATM
03SODATM
0160DATM
03700ATM
03SOOATM
03900ATM
0400DATM
04100ATM
0420DATM
0430DATM
04400ATM
0450DATM
0460DATM
0470DATM
04SODATM
0490DATM
-------
36
•>
6
7
H
'(
HI S( <"i I 161
HI S(,42( 161
H I S I U 1 I 1 f, I
OPTMI60)
,
t
,
HI Sf. )2 I
HI SC4 31
H 1 S T U 2 (
161
161
161
.rjVKIMI 501
(JUI tM,C(60)
UIMFNSUN
1
2
1
4
T|MF(60I
THKI 1)1 SO I
DAYSI2.31 ,
RKRHI4.2 ),
.CUI2I 300)
,
p
,
,
,
.TONAGM6) ,
t
TIMEUI2, 12)
IFICULFRE
10
1 1
12
13
Of.
Gil
TO 1
TO I
DSLC •
r.r,
TO I
OSLC «
GL
TO 1
osic <=
11
12
4 .
4
3.
4
2.
14 KSTMFS »
.fcU.3.1 GO TO
,11,11,12,12
.12,13,13,13
I SIMFSTMO. )
,
,
INCRMt = (Of LDn>« 10.0)
KTMOP =
TRL (60 1
I TIML (2
RKCC (4
.
,12)
,2)
,
, TNFTYPI50
10
12I.JUW
13),JI'H
+ 0.5
t 0.5
KSIMTS < (NOTRK'INCRMT I
HISC 331161,HISL 14116)>
<.<.( 16) ,HIST01 ( 16) ,
HISTU3(16).HISTUAI16).
PEHUNI4) .QUI50) ,
RQADIS(25),STAT(90)
TOTWUSO) .TRCI60) .TRIPI90I
TSrM(1000),WATE(50) ,
OUI TTMI50.6) , RKAA(<>,2).
TARtA(50,3),THALDS(50,3).
31. TNOHUNI50.3)
DIKFNSUIN LXI
CflU RANPFRILXiNOIRKI
INT = 0.
KKK » KTHOP - 1
Or, 30 I « KSTMFS, KKK
INT - INT « 1
NT = LX(INT)
JZI/10.0
fVENTINTI = 1
C«l_t_ CREATEI4, IRNn)
ITVPt2-FVENT(NT)
ITlMF?=TIMt(NT)
ICDRfitIDNO»3)«NT
CtLL CAU?t(ITVPF2,tONO,ITIMF2)
30 CT.NTINUE
PRINT 100
RFTURN
100 FCRMAT I 1H
mo
.32HTHE LAST TRUCK HAS LEFT THE YARD)
O'JOOOATM
05100ATM
OS^ODATM
05300ATM
0540DATH
0550DATM
0560DATM
05/ODATM
05BODATM
0590DATM
06000ATM
0610DATM
0620DATM
06300ATM
0640DATM
06500ATM
0660DATM
0670DATM
06HODATM
06900ATM
0700DATM
07100ATM
0720DATM
0730DATM
0740DATM
0750DATM
07600ATM
0770DATM
0780DATM
07900ATM
OBOODATH
0810DATM
OB200ATM
OR30r>ATM
OS40DATM
0850DATM
0860DATM
0870DATM
0880DATM
0890DATM
0900DATM
0910DATM
09200ATM
09300ATM
09400ATM
0950DATM
*IBFTC C/1SW*
SUBROUTINE OAYSUM
c
C COMMON AND DIMENSION FOR LIST PROCESSING ROUTINES
C
IDUG.ICALDR.IOECKilCLOCK.ICOREi IOUMM2 , I OUMM4 , I FRST2
CUMHON IFRSTA.lFRSTB.inVRHO.ITIMEl, I T I ME 2, I TYPE 2 , JBUG. JCHECK
COCf ON PAXCRF.MAXINT.MAXT.ITYPE1
OIMFNSION ICORE(ICOO), CORH50)
ECUIVALENCF(ICORF,CORE)
COfKON AND DIPbNSIDN FOR SIMULATION
COMMON /BO/ A9.ACRE.AM/M OS , ANF T YP , ANOHUN, ANORUT . ASNUPT .
1 AASSUN,ASSSON.ASSUNK,AX1,AX2,AVI,AY2,B,CCL.CLKTM,
COLFRE.COLHR.COLMLK.COLTMZ.COMPAP.CONA.CONB,
CONC.COND.CONF.CONF.CaSCOL.CORACR.COSLNDt
CRtWTS,CRUSZ,CSHRTC,CSTHR,CTS,DAYS.DELDEP,OMTAVE.
nMTMAX.OMTMIN.OMTSIG.OOLCOL.DOLRlG.OnLTON.
nOLTS.ORUPAY.DROVRT.OSLC, DM, EVENT, F INDAY,
FlATNO,FLTLTM.,FX,FY.HISC12,HISC13.HISCl NOTRL ,NOVRT1,NUVRT2,NOVRT3,NT,ONCE,OPTM,
6 ORHR,OVPAYL,OVRTM,PAYLBR,PERUN,PNDMU,PNDSIGt
7 PRBFLT,Q0.01.Q2.03,Q05,Q6.07,Q8,09,Q10,
8 Ull.OMAX.OO.aUIAVE.OUIMAX.CiUIHINiOUISIG,
9 QUITMC,OUITTM,OUT2,R,RGVMAX,RGVMIN,RIGKA
COMMON /BO/ RIGKB,RIGMAX.RIGVEL,RKA,RKAA,RKB,RKBB,RKCC.
1 ROAni S.RMXOSRiRMXOST.RND.RUNNO.SCOLMLiSMMRKT,
2 SRtGML,STAT,STMFST,STRFML,SUHRUT,SUMTRK,
3 TAREA,THALDS,TIME,TIM6Q,TNETYP,TNOHUN,
<. TONAGE,TOTCOS,TOTTON,TOTWT,TRC,TRCSIN,TRES.
5 TRFHR.TRFKL.TRFTMZ.TRrp, TRKOAY, TRKLO.TRL,
6 TRLHAL.TRPCOL.THPRIG.TRPTM.TSCOST.TSHR,
7 TSLnPA.TSTM.TX.TY.UNACRE.UTUTY.VELMAX,
8 VELMIN.VFLMOR.VI LMUT , VEl SGR, VEL SOT , HATE ,
9 WATFZ.WT.XIIAY.YRS
00100ASM
0020UASM
00300ASM
00
-------
37
AH A I I)'. I 7 ') I , AM IYI'l7t>),ANI)HUN(7'>>fANUMUTI7'>>i
A'.MIIM | 7'> I .AAV.IIM 75 ) ,A» I I 7S| ,AX?(75I i
AYII7S) ,AY7(7'>), HI 10 I .(.CL I 61 ,C(H Ml K ( <, I ,
l.ciPAfUI',1 .CISIfc) .FVFNU6UI .IUSC12I16),
HI SC I II 1 (.) .
HIV
HI S<
7lt6l.l
I SC 1 <. I 1 6 I , H I ', f. 7 2 ( 1 6 ) , H I S(. 7 3 ( 1 6 ) ,
ISf t?l 161 ,HISC HI 16) ,HISC 34U6),
1 M. 'i )( IM ,
I 1 61 ,111 STlll ( 161 ,
1 SIII7I 16 I ,HI SIU3I 16) ,HI SUM ( 16 > ,
IIIPENSII'N
Ul 171 K', I
17 ( C,K I I NDI
H I ', I U I ( 1 h I , I
OIMMI60I ,
I , NOIRK
• Ijl) I I IMI I ,.K)W I / 60.
t 51 , Nil IRC 2
*<. I I I »LI . XQH ) r,(J 10 666
(CHI1PCI I I - XOHI / 60. I • 1.
LT. 666
II- I OUI
IX Y 7 -
XY 7 - I
X YH = X
X Y 9 •- X
(166 C.f'M irillt
/NC1KC -i NOIRC
XY10 - 7NniR(. • 06
(.ISIIDWI = CTSIJDW) * A9 « XY9 * XY10
111 K NAC.I I JOW ) « Ml / 7000.
Kl IIIHN
f M;
0 M
OAHODASH
O^'KJOASM
osnnuASH
0510DASM
OS700ASM
0'> inoASM
K 1C l!l I Ml .1 U. 3. ) r,n TO 70
f.C 11! I t,H,l, H,hH, in, 70, 70 I , JDK
ft H < RI / S / - 4 .
f,l, 10 77
70 (HIS/ « ).
77 l;(l 101 = 1 ,N(1TKK
(Illinu) » C(IIJIIM) • I t!>THR>QU!TTMI I, JDWI/60. ) * DPDPAY •
I PAYI IIH • I CRIJS/ - 1 . )
10 { I M I Nil I
H lU'l.KJ.O. I GO TO 70
1)1 71 I = 1, NII1RK
((I I HIM) « LCIIJliM) »(UVHfMII) • DROVRT) • IOVRTMII) • OVPAYL •
I (CHU5/ - 1.1)
71 (.UNI INOF
70 IF I ASSMIN.f 0.0. I GO ttl 111
Of. M3 I « 51, N(IIRC2
msiiowt « CISIIDW) » (optMii) / 60.) • CSHRIC
i 1 i (,'IM INIlf
X Y') - 0
XIH = on • '.wo.
o*j f on ASM
0'iHODASM
05'»)IIASM
06000ASM
0610DASH
Of. 10DASM
0 6'' 01J A S M
0 6 l> 01) A *", H
Of.'.OUASM
06 (OI)ASM
0','iODASM
07 lOOA'.M
0770DASM
0 I (OOA'.M
0 740IJASM
07',OOASM
0 770DASM
0 fHOUASM
0790DASM
OHOODASM
OH100ASM
0870DASM
OS iOUASM
OH'iODASM
OH600ASM
OH700ASM
OHHODASM
OH'JODASM
0900DASM
O'HOOASH
0920DASM
0930DASH
09'iODASM
09".OnASM
0960DASM
09HOUASM
09900ASM
10000ASM
1010DASM
1070DASM
10300ASH
nor re i-f si«
SCJIiHIIU I I M-
c
C C(
c
OEStRY (NU^1, IDNII)
UPfON AND DIHbNSIUN FOR List PROCESSING ROUTINES
tnfwciH HUIC,, ICALUR, ICHtCK., 1CI 0(,K, I CORF., I OUMM2 ,1 UUMM'i, IFRSt 2
CIlPMUN l(RSI'.,irRST8,10VRH(l,lrlMFl1ITIMF2,IIYPfi2,JBUC,JCHECK
CncPON CAXCKE. >l>'AXINTlfAxr,ltYPFl
l)ll»rNSI(,N ILORFI1000), CURflSO)
FL1II VAI [ NU ( IC.ORE.COHr )
CnfPUN AM) OICEN510N FUR SIHULAI10N
CCCMIIN /IT/ A9, ACRE ,AHAt 1)5 , ANE I YP , ANOHUN , ANORUt .ASNUPT,
COLfRF,COLHR,COLf'LK,COLTMZ,CQMPAP,CUNA,CIINB,
CONC .rOND.CONF ,niNF .COSCUL .CDRACR.COSLNO,
r.PFWf,,rHIJi/,(. M'RIC.CSTHR.CTS.OAYS.IJEinrP.OMTAVE,
OCIMAX.DMtM IN.Iipr SIT,, DOLCIU ,1)01. R 10,1)1) LtON,
UOI [•,,l)IIIJPAY,l)«OVRT,[)'JLC,nw,F V! NT.F INDAY,
H1SC27,H1S( 7 1,111 ',C7'. ,HISC )7,H1SC t),HI ',C 3H, JIRC ,
ltRL,.IIR(>C.L,JTHI'Ur, ,K,K2,K<,,K5,KAPrS,KINrHK,
KlNIRL,KSIMI!),KIMni>,HAXLO,NA,NARtAtNC,NDA,
NDH.NN.NLIRUt ,NOI l T S , NO f RC , NOTRC2 , NUTRK ,
NrtKlIN(IVRtl,NIIVRI2,NnvKf3,Nr,ONCF,riPtM,
00100EST
00200ESI
0030DEST
00"iOOEST
00500FST
0060UEST
00700FSt
OOHOOtSt
OlOODESt
01lOOFSt
0120DEST
0130ntST
Ol'iODESt
OlbODESt
0160DESt
oi/oorsT
01BOOFST
0190l)ESf
0700DEST
OZlODFSt
0720l)FSt
0730»FSf
07700FSI
07HOOEST
07'lOOtST
OMIODFST
-------
38
6 IJUHR.HVPAYL.IIVK'tM.PAYl M.H , I'E RUN , PNOMU . PNOS I G , UMOMI-ST
I PRI1II ! ,UO,OI ,07,1)1, (14,05,06, 07,00,09,0101 0320DFST
H Ul I .OMAX.CU.UDIAVt , UU I MA X , Qll I M I N , OU I S I G , 03300FST
'I UIII IM'.,UUI MM,OOt2,K,RGVMAX,RGVMIN,RIGKA 03<.OUFST
MlpmiN /Ml)/ R| (,KH,H I(,MAX,R IGVF I , RK A , RK AA , RKB , RKHH , RKCC , 03500FST
I RUADI S,R«XUSH,RHXI>ST,RNO,RUNNO,SCOLML,SKWRKT, 03600FST
2 SRI'. Ml .STAT.Sim SI.STRFML. SIIMRUT , SUMTRK , 03fOI)FST
3 IAKFA,IHA1 OS, TIMF, IIHEO.TNETYP, TNOHIJN, 03BOOFST
'« TDNAf.F , KllCriS, TO r ION, Tni HI , TRC , TRCS I N, IRF S, 0390DFST
5 IRHIR , IRFML , TRFTH/. , TRIP, THKOAY, TRKLO, TRL. 04000EST
6 IRLHAL. THPCIII.,TRPRir,lTRPTM,rSCGST,TSHR> 04100EST
t I SI I1PA, MTM.IX, lY.UNACRF.UTILTY.VELMAX, 0470DFST
« VH MIN.VFLMUH.VI I MUT.VELSGR.VFLSGT.WATF, 0FST
9 WAIf ; ,W1 ,XUAY,YKS 0 I , ANflHUN I 2 5 I ,ANORUT(Z5), 0<.SOnFSI
I A'.NUIT (i"i) , AASSUN(?5I,AX1I25I ,AX2(?5) , 0460IJFST
? AY1(^5I .AY?!?1!), Bl 10) ,CCL (61 ,CnLMlK(<,) , OWOOFSI
? I)HA(RI'.| ,CIS(6I ,FVENri60> ,HISC12(lfc), 0(.22( 16 I, HISC?1I 16) , 0,HISC3, OiOOIIFSf
h HS(,'.?( 161 ,IU',C«i( 16l,HISC« O'j'.ODFST
IIICFN'.IIIH 1IMM60I .TDNAf.MM .TllTUnSO) ,TRC(60) ,TRIP(90I t OSSOOFST
I TRKII;(50) ,TKL(60) , I SIMI 1 000 I , MATE I SO I . OShODFST
/ DAYS!?, 3), IIIMl(?,12l, OH I I I M ( 50 , 6 ) , RKAA(<1,<>I, 0")fOOFSr
1 KKHHK,,?), RKCCI<.,2),IAHi:AI50, 3 ) , TIIALDS I 50, 3 ) , O^flfJDFST
'• MMFUI?,!?), INFIYPI 50, 3) , TNOHUNI50.3) OI'yODtSI
1 1; -I UNO
IMNIIM-H) I00,?00,600
200 TALL f II F',1 I ID.fi, IFRSI8I
'.H HI SCO
100 1FIMIM-4I (00,101,600
inl |M ]( f)HI | lU»M-lniJPP4) 102,105, 102
102 IF ( ICI1RH IU-3)~H)UKM<, I 103, 104, 103
10) fAll F II F SH ID, 4, |F«W ll; = ll)-
-------
39
c
c
c
c
c
c
c
c
c
II
c
c
c
c
c
(.
c
f.f'MMDN / h|)/ A') t Al Ht , AHAI IJ S , ANf 1 YP , ANUHVJT4 , AN1JHD1 , ASUUIM ,
1 AASSIIN, ASSSUN.ASSUNK ,AX1,AX?,AY1,AY2,B,CCI , CLKTM,
? Gill 1 KF.CM1 HH.UllMl K,CrilIH/,COMPAP,CuN».r.l)NH.
1 CfJNI. ,( UNII.C I.NI ,(.IINf , COSCCIL ,'.(IRAf. R.CUSI Nl),
* (RtHlS,(«US/,CSHKTC,CSTHR,CTS,OAYS,OELOFP,OMTAVF,
•> DM I MAX, DM TM IN.DMISIG , DOLCHL , DDL R 10,001 TON,
6 mil IS.OKUPAY.IJROVRT.DSI CiDW, EVENT, FIND AY,
1 FLAINri,fLTI IM,F X.FY.HI SC12.HI SCI ),HI SCI*,
H HISf 72.HI ST. ? >.HISC?*.HISr 3 2, H ISC 3 3, H ISC 14,
9 H1SC*2,HI SC*3."I SC**
rr'PMON /HI)/ HISIDl.HI SIU1 ,H1STU2,H1S1U3,H1 SIU*,
1 1C HI FR, IN, INCRM1.IUU, IRUNN.0,1 TIML, JOW, JTRC,
2 JTRI .JTRPCI , JIRPRG.K , K2 ,K* ,K5 , KAPT S ,KI NTRK ,
( KINTRI,KSTMFS.KIMnP,MAX10,NA,NAREA,NC,NOA,
* NOR.NN.NnRUI.NOf L1S,NUTRC,NOTRC2,NOTRK,
5 MflTRL ,NHVRr UNIIVR T2,NOVRT 3,NT,ONCF,OPTM,
ft ORHR.uVPAYL.nVRTM.PAYLBR.Pf RUN , PNOMU , PNDS 1 G ,
I PRflll rlQOlUll()?lU1,Q*,0^,Q6,U7.U8,gq,010,
H U11,UMAX,UU,UUIAVF,OUIMAX,QUIMIN>UU1SIO ,
') QU1IMC ,QUI F fM,(JUtP,R,RGVMAX,RGVMIN,Rir,KA
(.flKMUN /III)/ Kir,KH,RlGMAX,RIGVEl ,RKA,RKAA,RKU,RKBH,RKf.C,
1 RdAUl S,RMXUSH,Kr«XDSt ,RN[), RUNNO, SCOLML , SHWRK T ,
2 SRlr,ML,STAT,STM(ST,StRFHL,SUHRUT,SUMTRK,
3 TAKTA, THAI DS, TIMI, TIPFO. TNI- TYP , INOHUN ,
". mNAf, E, TOTC HS.tCII TON, InTWT, IRC, THCSIN.TRES,
S IHFHP,TRFML.IRF1)*;,TRIP.1RKUAY.THKLD.TRL,
h TRLHAL.IRPCOLtTRI'RlGiTRPTMiTSCOSTiTSHR,
f JSlHPA,!STM,fX,TY,UNACRF,UULTY,VELMAX,
H VFLMIN.VbLMUR.VriMUI.VFlSGR.VFl SOT, MATE,
1 WAIT / ,HI ,XI)AY, YMS
IllPf NS KIN AHAll)S(Z''>,ANFTYPIZ5) , ANQHUNI 251 ,ANORUTI?5)
1 ASNUl'T 1 2"il,AASSUN(25l,AXl 125) ,AX2(?5)
2 AYll2-il ,AY2(25I, fl 1 101 ,CCl 1 6) ,COLHLKI* 1
3 CORACRIAI ,CTSI6I ,FVFNri60) .HISC12I16)
t> HISCMII6I, HI SC1*I16I,H1SC 221161, HI SC 23116)
•> HISC2AI16),HISC 321 16) ,HI SC 33(16),HISC3*(16I
6 HISC*2ll6)>HISC*3ll6),HISC**ll6),HISTnlll6)
7 HlrilUI(lt),HISTU2(16l,HISTU3(16).HISTU*ll6)
H HPTMI60I ,()VRTHI50I .PERUNI*) ,00150)
'1 UUITMC l60l,OUr2(300l,ROADIS(25),STATI90)
OlfFNSIIN TIMH60I ,T()NAGtl6l .TOTWTI50) .TRCI60) .TRIPI90) ,
1 IRKIDI50I .TRLI60I , T STMI 1000) , KATE I 50 ) ,
? OAYSI2.3), ITIMLI2, 12) , UHITTM(50,6I , RKAAI*,2),
3 HKBBI*.?), RKCCC.,2I,TARFAI50,3I,THALDS(50,3) ,
« HMFt)(2,12). INF IYP 150. 3) , TNOHUN150.3)
1)11 ONI: TIME INITIALIZATION AND PRINT TABLES ONE » TWO
CM L RUNUAT
C 4LL /CRINT
CALL TAtH 1
CAIL TAH12
CALL TBLPRN
00 IllE SIMULATION FOR SIX DAYS
ur 28 I = 1,6
JCH * I
CM I XINIT
CML IK 111
CALL OATCAK
CALL T 1 V f R
CAIL DAYSIJM
2H COM INUE
SUf^ARI?fc FOR THE HFIK AND PRINT THE FINAL SUMMARY OF ANALYSES
CAIL WEtKSM
CAIL FNLPRN
KtTIIKN
END
BFIC CSPSL'
MJHRIIIJTINt- OISPSLUDNO)
COCMUN AND OIChNSION FOR LIST PRCCESSING ROUTINES
COPMIJN [DUG, ICAIUR, I CHECK, 1 CLOCK, 1C ORE, IOUMM2, IUUMM*, 1FRST2
CCVMUN IFRSt'i,IFRSI8,IOVRHn,ITIMEl,ITIME2, I TYPE 2 , JBUG , JCHECK
(0PM UN PAXCKL,MAXINT,MAXF,|IYPE1
DIKFNSIUN ICOREIIOOOI, CIJRFI50)
FCUIVALFNCFIICOHE.CORF)
C.flfMIN AND UIWENSION FOR SIMULATION
CDfMIIN /HU/ A1, ACRE ,AHAI OS, ANF T YP , ANDHUN , ANORUT .ASNUPT,
1 AASSUN,ASSSUN,ASSUNK,AX1, AX2.AY1 ,AY2,B,CCL,CLKTM,
? CfJl FRF .CHLHK.r.HLMLK.COLTMZ.COMPAP.CUNA.CnNB,
) CONC ,COM),CliNF .CONF.CDSCHL ,CORACR,CUSLNO,
<, (RFKTS,CRUS/,rsHHTC,CSTHR,CIS.OAYS,r)MI)FP,OMTAVE,
OlSd OKI
0160 ORI
0 1 10 OR I
01BO DRI
0190 DRI
0200 DRI
0210 ORI
0220 ORI
0210 ORI
02*0 DRI
0250 ORI
0260 DRI
0270 DRI
02HO ORI
O2')0 DRI
0300 ORI
0310 ORI
0320 DRI
0330 DRI
0)40 ORI
0350 DRI
0360 OH I
0370 ORI
03HO ORI
03^0 ORI
0*00 DRI
0*10 DRI
0*20 DRI
0*30 ORI
0**0 DRI
0*50 DRI
0*60 DRI
0*70 DRI
0*80 DRI
0*90 DRI
0500 DHI
0510 DRI
0520 URI
0530 DRI
05*0 DRI
0550 DRI
0560 DRI
0570 DRI
05BO ORI
0590 ORI
0600 ORI
0610 DRI
0620 DRI
0630 DRI
06*0 DRI
0650 DRI
0660 ORI
0670 ORI
0680 DRI
0690 ORI
0700 DRI
0710 DRI
0720 DRI
0730 DRI
07*0 ORI
0750 DRI
0760 DRI
0770 DRI
0780 ORI
0790 ORI
0800 ORI
0810 DRI
0820 ORI
0830 DRI
08*0 ORI
0850 DRI
0010 DSP
0020 DSP
0030 DSP
00*0 OSP
0050 OSP
0060 DSP
0070 DSP
0080 DSP
0090 DSP
0100 DSP
0110 DSP
0120 DSP
0130 DSP
01*0 DSP
0150 DSP
0160 DSP
0170 DSP
0180 DSP
0190 OSP
-------
I (IPMI1N /III)/
UM1 MAX, I.MIM IN, DM I Sid, Dill COt .OOLH I (, ,()UL ION,
11(11 I ', .III'IJI'AY.IIRIIVW I .DSIC. ,I)W,F. Vf N! ,F INDAY,
F I AI'll], Fl Fl IM,F r ,F Y , HI SC 12. HI SC 1 ),HI SC 1 4 ,
HIM 2 2,1'ISC 2 ),HI sr.24,HISC t2,HI SC )3,Hl SC34.
HI S( 4 2, I'I St. 4 i,HI 'j< 44
HI s 111 I ,l'l S Fill ,HI SFU2.HI SIU),HI STU4,
I (.III I H, IN, INCHM! , IUU, IRONNO.I TIML.JOH.JTRC,
JIRI , IIKPCI , JIH P R G,K,K?,K4,K5,KAPTS,KINTRK,
KIN 111 I , 1C, IMF S,K!POP,PAXLO.NA,NARfA,NC.NOA,
NI)H,NN,NURUF.NnllIS,NOIRC,NOTRC2,NOTF»K,
NOIKI ,NIIVR F 1,NOVRT2,NOVRI3,NT , ONCE ,OPTM,
IJRHH, UVPAYI ,(IVR IH.PAVLIIH , PE RUN , PNDMU , PNfJS I G .
PR HI I 1,111, 01,02,03,04,05,06,07.08,09,010,
011,OMAX,UO.OUIAVEiliUlMAX,OUIMIN,OUISIG.
Ulll IMC ,1.01 IFM,OUI2,R,RGVMAX,RGVMIN,Rlf,KA
( OK Ml IN /IM)/ RI(,KII,KIGMAX,R|(,VEL,RKA,RKAA,HKK,RKBH.RKCC,
HIIAIJl S.RMXOSK.RMXDST .RNO.RUNNO, SCOLMl .SMWRKT,
Snn,Ml,STA\,STMF',TfSTRFML,SUMRUI,SUMTRK,
lAHIA.riiALUS.TIMf.FIMEO.TNFTYP, FNOHUN,
DIPf N1KIN
I) I fl NS II N
IHFHF(,IRFML,THFIM/,FRIP,IHKDAY,TRKLD,TRL,
FRLHAl , TRPCUL.TRI'RIG.TRPTM.ISCFJSI, ESHR,
ISUiPA.ISIM.IX.IY.UNACRE.UTILTY.VELMAX,
VELMIN,VEIMOR,VFIMUT,VEISGR,VELSGT,WATE,
WAII/,HF,XOAY,YRS
AHALUSI21>I,ANETYCI25I .ANOHUNI 25).ANORIiT(25),
ASNUI-TI25I , AASSUNI 251 ,AX1 1251 ,AX2(25) ,
AY1I25I .AY2I25I, BI 101,CClI 6),CUlMLK(4 I ,
CURACRI4) ,CTS(6) .EVENTI60I .H1SC12I16I,
HISC13(16l,HISCI
IHKLUI51) .TRLIAOI .TSTMI1000),MATE I 50) ,
I1AYSI2.3), IIIMLI2.12). OUITTMI50,6), RKAA(4,2I,
RKHIII4.2), RKCC(4,2),TAREA(50,3I,THALDS(50,3),
IIMFOI2.12I. INF FYPI50,3), INOHUNI50.3I
OTIMFI2),N1NO(2I
291
tl
IF II.H.F 0. I . I GU Id 1
llh 1 .
tF IPI I 1 I=0.
Cl IMI I 2) 0.
NINOI1)-0
N I N 0 I 2 I - 0
K 2 H I G = 0
F I N I) A Y = 0 .
lir M - 0
IF I ASSSI'N.Nf .?. I GO TO 906
IF I I FYPf 1.F0.5) GO TU 30
RNO = HNMUO) • 100.
(ALL HIS!(HISTUltRND.Y)
DKPIM7 - Y
lid 29 1=1,2
i r, = i
IF (NINO! I I.fO.OI GO TO 36
fINFINUI
IF (NINUI 1 ) -LF.N1NO(2 I I I0«1
( I M INUE
I'MNOIl l!)*l
11 I I. r, i . i i I | . 12
xic = 111 MI i-ir i MI do, i i
i IKI on r, i i-TiMFOiin, i) «xic
IT Ifl II II, I I •>! I IMH
I I (Ml II F), I » 1 |. I I IME 1
Ml NCI I II I -NIM_( 10) > 1
II (NINC II I) I .GI.MAXIOI MAXI O'NINOILDI
01 IMF II I: I-LI m II 0) illMIMM/
MCI (N! I -CI IMI I t I) I
IVFNI(Nl]"S.
fAII
1 1 (,CI
I (. ( R I
If CHI
( I HI
(,T IU
K NO )
HI A IF I «, IIINini
I (. Nil* / I « I (JI40 1
I 1 1 N I 1*1) LI)
I I.M, )«2) = I ! IMF 1
I I, Ml H)| 3|)MPTH2
ICC?
ICdKFI IHNO'2)
Ll: = l(.ORE I I UNO 3 » 1 I
ITPINMU/REI IDNtm?)
RPPTWZ- CORE! IUN03+3I
CALL OtSIHYIA. IDNQ3I
i«MNCI II l»l
I F I I . G T . I 1 ) I * 1 2
OTf' IT IMF 1- I TMN
CFt-'UFM-l MPIMZ
TlftLlLL ,l) = !lf«FO(LD,|)tF'. OATI1
TIME1-ITIMLILO,I I I
o <• o (i o s p
0210 DSP
0220 DSP
0230 DSP
0240 DSP
O2')0 OSP
0260 DSP
02TO OSP
02BO OSP
0290 DSP
0300 DSP
0(10 OSP
0)20 DSP
0)30 DSP
0)<-0 DSP
0350 DSP
03ftO OSP
0370 OSP
OiHO OSP
0390 DSP
0400 DSP
0410 DSP
0420 DSP
0430 DSP
0440 DSP
0450 DSP
0460 DSP
0470 OSP
04flO OSP
0490 OSP
0500 DSP
0510 OSP
0520 DSP
0530 DSP
0540 DSP
0550 OSP
0560 OSP
0570 DSP
05HO DSP
0590 DSP
0600 OSP
0610 OSP
0620 DSP
0630 DSP
0640 DSP
0650 DSP
0660 OSP
0670 OSP
0680 DSP
0690 DSP
0700 DSP
0710 OSP
0720 DSP
0730 DSP
0740 OSP
0750 DSP
0760 OSP
0770 DSP
0780 DSP
0790 DSP
0800 OSP
0810 OSP
0820 DSP
0830 DSP
0840 DSP
0850 DSP
0860 DSP
0870 DSP
0880 OSP
0890 OSP
0900 DSP
0910 OSP
0920 DSP
0930 DSP
0940 DSP
0950 OSP
0960 DSP
0970 OSP
09HO OSP
0990 DSP
1000 DSP
1010 OSP
1020 DSP
10)0 DSP
1040 OSP
1050 DSP
1060 OSP
1070 OSP
1080 DSP
1090 DSP
1100 OSP
1110 OSP
1120 OSP
-------
Ml N'_ I M, I M Mjl I I I I
I I I fl I I I , 1 I I T I'M 1
I ! l"l II I , I I )• I I IMf I
1,1 III 1/7
(.! Iff (I I I I T [HI 1
I.I II! /"I I
I SCK • I'.HP • (If-PIW; > UIM
Tm'Ull - IRPf ()L • I .
K,- • K? • 1
ir, i *i K? i » I;MP (*/ • UTM
f t K I P I I M F ( N 1 I
I f i AV.MIN.I . I r,n rn 905
I w I'I III I P I'LIM * 1 .
c ;• = K ^ > i
I'M, • HM «l 0 ) • 100.
(All I'l S I I M I ST(> I ,«NHt V)
T S H R * I M < R «
1SIMK.II CMPIH7
Cl K IM = I If! INT 1 » DMPTMZ
90S I f I I.UI N! I .1 U. I . I GO TO 17
F V [ N ! I N I I --- 1 .
t I K [ t N M * CIKTM
(,l III 44
); ci, t MCI N! , JUKI * r t KTC,
K U H K - 0
II I I 1 K I F .11 .4 HO. ) CD 11) HO
I)VRI^/. ' (IlKTM - 4fiO.)/60.
111V H I M - I ] V R T M Z
III VK I M - II,VRTM
M d.VRTC/.l F .IMWR.TMI GO HI 401
405 OVU I MN I I = JI1VRTM « I
f,( III 40'J
401 HVRIfINI I - JOVRTC
409 IMP * IVRTCINII
II I JKI P .(,T . ? I GOT (I 7 9
r,l Illl ( 7. 7H) , JKl M
7 7 Nf VR I I ' NIIVHT 1 • 1
f,l III 44
7H NI VR I ? ~- NIIVRT? > 1
l,f 11144
79 NI VRT 1 - NIIVHT 1 » I
Gl TO 44
flO IJRIM " (4HO. - CLKTO/2.
ORHR = DKHH » OMTM
44 RIGIlin -- KIGICIJ * TRKLDINT)
If IK IGLIiU.l T .R 1GMAX 1 GO 10 999
M I f, I I) I > - 0
1,1 22? I >= 71,90
IF ISTAIIl).EU.ll.) GO TO 241
222 r CM INUt
MR I Tl I ir.U, 10)
241 JTRI = I
S,T A I I IT V L I - 1 2
1)11 Mil I > 71,90
If (STAII I I.EU.10. I GO TO 24 7
)01 rrM INUt
WR I II I III], 10 )
10 (DRMAII 1C-,34HIMPOSSIBLE THAILEH STATUS IN DSPSL I
?4 ! STATI I ) = 13
111) 121 I *• 51.NIIIRC2
I I I', I Al I | | .1 0.8. I GO TO 909
12 I H'NI INIII
Gli Tfj 999
'>H9 TUT I J I - J
IRl I I I«J1RL
S I A I I J I . 9
STATI ITRl | i 11
999 IfIK2R1G.EO.O.*ND.K3TRK.EO.CI GO TO 1000
IF IK 1TRK.rQ.Ol GO TO 1001
If(K?RIG.FO.O) GO TO 1002
CALL CKFATEI4, IDNO?I
MYI'E? • FVENTINTI « .5
IT ICF? = TIMHNT) * .5
If!RE(1HNT? » 31 i NT
CALL CAUSE I ITYPE2,IDN02,ITI ME 2 I
GC TO 1001
1000 FINL)AY = 99.
GC Til ICO?
1001 NT =J
IVENTINT1=7
T I M INI I -(IKIM»5.
100? Rf I URN
I UK
1 1 10 DSC
1140 DSP
1 1 S 0 0 S P
ll/>r> DSP
1170 DSP
11BO OSP
I l'»0 DSP
1?00 OSP
1?10 OSP
12?0 DSP
1?30 DSP
12 0 DSP
l?/jO OSP
1270 DSP
1? H 0 DSP
l?r<0 DSP
1 )00 DSP
1110 DSP
11?0 DSP
1 )10 USP
11<.0 DSP
1 ISO DSP
1thO DSP
1170 DSP
11HO DSP
li'in DSP
1400 DSP
l<.in DSP
14?0 DSP
1<,10 DSP
1<,<.0 DSP
lA'iO DSP
1460 DSP
14^0 OSP
14HO DSP
1490 OSP
1500 DSP
1510 DSP
1520 USP
15)0 DSP
1540 DSP
1500 DSP
1560 f)SP
1570 OSP
15HO DSP
1590 DSP
1600 OSP
1610 OSP
1620 DSP
1610 DSP
1640 DSP
1650 DSP
1660 DSP
1670 DSP
16HO OSP
1690 DSP
1700 DSP
1710 DSP
1720 OSP
1710 OSP
1740 DSP
1750 DSP
1 7/,0 DSP
1770 OSP
17HO DSP
1790 DSP
IflOO DSP
1B10 DSP
1R?0 DSP
1810 OSP
1840 DSP
1850 OSP
18ISO OSP
1B70 OSP
IHHO OSP
1S90 DSP
1900 DSP
1910 DSP
1920 DSP
1910 DSP
1940 OSP
1950 DSP
1960 OSP
1970 DSP
19HO DSP
1990 DSP
2000 DSP
2010 OSP
-------
FILF-
StlimiJlIF IM
', ( I I I; NO, I (', l( MM
( Off UN AND OICFNSKIN FOH I I SI PHfjCtSSING ROUTINES
f( CHUN I HIK,, ICAI I)K, 1C HFfK, |CI (!CK , ICURE, 10UMM2 , I OUCM4 , I F R S I 2
niCMllN IIKSU.IIHSIH, IflVKIIU, ITICM,IT[MF2,IIYPE2,JBUr,,JCHFCK
C f 1C CON KAXCHi ,HA(INI,MAxf,l|YPf 1
DIKfNSII'N ICOKF I 1000) , UJHFISO)
I cui VAI IN( F i irum ,r.f;«F I
( (IPPON AND DlfFNSION FnK 1IMHAFION
( <;PHON /III)/ A<), A< Rf ,AHA( IJS.ANF T Y P , ANOMUN , ANORU F , ASNUPT ,
I AAS',IINIASS'>UNtAVjUNK,AX|,AX?,AYl,AY2,B,CtL,CLKTN.I
2 COL MF ,( 111 HK ,C(>1 Ml K ,COL T M7 , C OMP AP , C(IN A , CUNB ,
i r.(jNf ,n,M),(.uNi .rMNF.rnscoL.coHAf.R.cusi NO,
4 fnitvi1, ,r«m/.r vwrc , <. snm,crs,DAYs,r)FL(jEp,o«rAVE,
5 Uf IMAX.OMFMN.DMISIG.OOLCUL.OOLR 1C, DHL TON,
6 l)(ll TS ,I)K(>PAV,IJKOVR I , I; S Lf. , D W , E VFNF ,F 1NOAY,
7 HA1Nn,riTLIM,hx,fY,HI<,C12,HISr. MiHISCH,
n H isc??, cisc ? i. HI •>(.?'., HI sr. 12, HI sr. n, HI sc3<. .
<) HI r>C«?,H| SC<,lrHI SC«A
CIJfMllN /MO/ HISInl.lllSIDl.HI <,TU2,mstlJ3,HI STUN()VKr2lNnvRr3lNT,()NCE|[)PTMl
h IIRHM.OVPAVL ,(IVR Tf.PAVl BR.PEKUN.PNDMU.PNDSIGt
1 PRIIII r.UO.alfU?.01,04.05.U6.07fUH,a9i010i
H Ull.uMAX.CU.UDIAVF.IJUIHAX.UUlHlN.QUISICi
'I Oil I I MC.OU I T IM,OIJT?,KtRGVMAX,RGVMIN,Rlr,KA
CCCMDM /HI)/ K ir.KR.R IGMAX.R l(,Vf I , R K A , RK A A , RK II . RKBB , RKCC .
I «f)A[)| S.RMXUSK.RfXOSI , RNO.HUNNC), SCOLHL , SMMRKT,
? SRI(,ML,SIAI,S[MI',r,StRFML,SUMRUr,SUMtRK,
1 r/UfA,THALI>S,tlMI,T I MFO , TNf T YP , TNOHUN,
4 rriNAni , rorr.uSi rui lUNtiorwi, TRC,TncsiN,TRiSt
•> IRrHH.TKFML.IKFTMZ.FRIP.IRKnAY.THKLO.TRLr
6 IRLHAL.IHPCIJL.FKPHIG.rRPTM.TSCOST.TSHR,
f FMMPA,ISrMtrX,FY,UNACRt,UFILTY,VFl.MAX,
IKFNSK.N
HATF/ ,Mt , XOAY, YRS
AHALIJSI25I , ANF F YP I 2 5 ) , ANOHUN ( Z5 ) ,ANURUn?5) ,
A',NUPF(;>S),AASSUN(25I,AXII25I ,AX2(25) ,
AYK?1;! ,AY2I?5), B( 16) ,CCL ( 6 ) , COLMLKI « I .
(.ORACH (<, ) ,CI5(6) ,EVFNri60l ,HISC12(16)(
H|5CMI16).HISC1',I16),HISC22(16),HISC23(161,
HISC2<.IUI,HISC32(l6),Hlsr, 33(16), HI SC14I16I,
202
201
7 HISFU 1(16), HISTU2(16I>HISTU3I16I
6 OPFMI60) .OVRFHI50) .PFRUNC.) ,00(50)
t OUI T MCI 60 I ,UUI2( 100) .RDAOISI25) .STATI90)
FJIPENSION riMEIbO) ,FONAGF(6I ,TnTMT(50) ,FRC(60)
1 TRKLDIHOI .TRLI60I , T SFM I 1000 I , WA IE I 50 1 ,
7 UAYS(2,3), IFIMLI2,!?), 01)1 T TM( 50.6 I , RKAA(*,2>
) RKBII«i,2), KKCC(
-------
i I NKUN AM I i I Ht V, I m, I ()*' '• I P »\ A 1 S MM
/I'I1/ A'), A( HI , A MAI I!', , AM I Y P , AMI 1IIUN , ANdklJ T , A SNUP T ,
1 AASMIN, A1. SSUN.AS SUNK, AX 1.AX2, AY I,AY2, I! , U L.CLKIH,
i ( III I m ,1 (II Mil ,( 1)1 f | K ,( (II Th-/ ,( OKPAP,(.ONA,rnNFI,
i I ( N( , f I'NII.r I Nl ,( (iNf ,( 1IS( I'l ,( OR AC R,( (ISlNf),
* (PIWIS,rillJS^,(SII'F(,fSTHH,CIS,UAYS,l»lDFP,D*TAVF,
5 I If If A» ,1 HIM IN, I If IS 1C, ,1)01 ( (II ,1)01 V I (,,!)(II TON,
ft I dl I S . OKI) PAY, Ok (IV R I , l)Sl (. , I)W,I VI NT ,F IMJAY,
7 I I A 1NO, F I FL IM,F X ,F Y,HI SC 1 2.HI SC M,Hl SCI*,
H HI ',( 22 ,H1 SC 2 3, HI ',f 2*, HI SC 32 ,HI SC U, HI SCI*,
9 IM SI *2,HI SC'i i,H I '.( **
( (If PON /MO/ H I', I I) I . H I S F I) 1 , H I S 102 , H I S Ft) i ,H I S I O* ,
1 l( (Jl I U, IN, IN( PH I , I (HJ, I « ON NO, I T I Ml , JUW, JtRC ,
/ IF PI , lIRPr I , JlPPIir, ,K ,K2,K*,K5,KAPIS,K INlRK,
t K IN I HI ,K<, If I S,K IMDP.fAXI Q,NA,NAPFA,NC ,Nl)A,
'i NI,R ,MN,NOIUH ,NOI I f S , NO I RC , Nl) T RC 2 , NO TRK ,
', NMP.I ,NOVR I 1 ,UOVH I2.NOVH I 3,NT ,IIN( F ,01'FH,
6 1 in Mil, IIV I1 A Yl. , IIVK IH.PAYl IUI ,P( R ON , PNOMU , PNOS I 0 ,
7 PCHII I ,1.11,0 I ,02,0 t,U'',05,U6,U 7,UH,09,010,
l| (j|l,(jMAX,U(J,binAVIlUljlMAX.UI)lHIN,UUlSlC>
9 UIJI I HI. .LI) I I I M, (JO I 2, H ,RGVMAX,II(,VMI N,R K,KA
1 I fPII'1 /!'(./ H I(,KH,H I(,f AX,P U, VF I ,kKA,kKAA,KKlt,KK»H,RKCC,
',« I I, Ml , ', I A 1 ,SIf I SI ,STHI Ml , SDK RUT , SUM! UK ,
lAUIA.THAlOS.tlfl.TIftUiTNfTVP, TNdMUN,
|r NA(, 1^ , KITf IIS, IDMUNi lOTHf i TRC , T HC S I N, I Rf S ,
IPIIM',rPIML,ll'IN,VllMllKtV[LHUt,VFl'.r,R,VtLS(.tIWATE-I
WATIf.WT.XDAY.YKS
IllfFNSION
ASNUI'M fi I , AASSUNI ?SI , AX1 ( ?5) ,AX2I?S) ,
AYH^'J) ,AY<>(2'j), HI 101 ,CCL(6I ,C(ILMIK(*I ,
(IIRA(RCi) .CISI6I ,FVE-NT((>0) , H I SC 1 2 ( 1 6 I ,
II1SC1 31 16) ,MIS(, 1A( 161 ,HI SC22I 161 ,HI SC2K 16) ,
IIISC2'. ( 161 ,MIS( 121 IM ,HISC )3( 16) ,111 SC >*( 16) ,
HI Sf W I 16) ,HI SI" '. )l 16 ) ,HI SC'tAI 16) ,HI SfUl ( 161 .
IUS1I)1(16I,H[S!U?(16),HISTU3I16),HISTUA(16),
IIPTMir.O) ,flVKIf(SO) .PhmiNC.) ,00(^01 ,
OUIIMC(60ltUUT?(300),ROADIS(?5),irAT(90l
TIMM60I ,niNA(,M6) .TOTWTCiO) ,TRt(60l .TRIPI90I
rRKlblSOl .TRIUiOl , I STMI 1000 I ,HATC (50) ,
UAYSI2,!), IUMI . UUI TTHI50,6) , RKAA(*,?I,
RKRHI't,?), RKrr. 1*4, ? ) ,TARF A{ 50, 3) , TMALOSI SO, 31 ,
12l. INh 1 YP( 50, 31 , TNOHUN(50,3)
?0?
201
I fill 1 1,1 I F K I 11 Nl.)
< Al 1 UM'ATKt 1PWN, IF IRS! .I.ASI I
IMl A',1 ) ?00,?00,?OI
< Al 1 PA( K( II;HN, IONU, ION!))
IX <- I [INI,, IP
I f ( II I I I X X I 0
PI IIJHN
i x x -• i u N r, » i p
(All PA( K( I (,I)RF ( IXX
IT X = L AS I « IP
(All UN I1 A( K ( ICOPF ( I XX
1 X X • ( A S I t I P
(.All I'A( K( |(.(IRF I IXX
(ill PA(.KI II WN, If LRST , 1 [INO )
(,( 10 202
I NF,
),IAST,0)
I.JP.IIJNO)
01 ill ( I
0 I ^ 0 F L
0150 FI
0160 Fl
01 111 F L
OIHO FL
Ol'iO FL
0200 F L
0210 FL
0220 FL
0230 fL
02<-0 Fl
0250 H
0260 FL
02rn FL
02HO F I.
02'IO Fl
0300 FL
0310 Fl
03JO Fl
0330 M
03<,0 FL
0350 Fl
0 )60 fI
0370 FL
03HO Fl
0310 FL
0520 FL
0530 Fl
05*0 FL
0550 FL
0560 FL
0570 FL
0580 FL
0590 FL
0600 FL
0610 FL
0620 Fl
0630 FL
06*0 FL
0650 FL
0660 FL
0670 FL
0680 FL
0690 FL
0700 FL
0710 Fl
0720 FL
07(0 FL
07*0 FL
0750 FL
0760 FL
t IBF 1C F II K"
SUFIROUF INF I 1LRNKI I UNO, IHANK, IP, ICWN)
<.I;PPIIN AND niprNSirjN FOK LISF PROCESSING RouriNts
IdCfllN I mil., 1C At OR, I (. HFCK,H.LOCK,ICORE,IOLIHM2, IDUMM*. IFRST2
( Off I IN II H', I',, IFRSTfl, invRHO, I TIME 1, ITIMF2, I FYPE2.JBIIG, JtHECK
(liffdN fAK(HI,MAX[NF,HAX!,lIYPf-l
I.IPINS1IIN KIWI (10001. UIRI(SO)
I LUI VA1 FN( I (ICDRl-.CnRE)
(.( PKIN AM (UPtNSinN FOR SIfULAItON
COKKUN /HI)/
A9, ACRE , AHALDS.ANE TY
AASSUN.ASSSUN.ASSUNK
C.OLFRF,C()LHH,COLMLK,
crNC.COND.CONF ,C( NF ,
CRIKlS,C«uS<[,CShRTC,
[)P IMAX.O"' TMIN,!. MTSIO
OnLTS,n«I]PAY,OR(iVRT,
F I AltJU.FI TL [M,F X , F Y ,
Hisr 22, H ISC 2 3, H ISC. 2*
Hi s( *2,l
-------
HIM , I I »!'C. I , IIHI'"I,,H,K?,K*,K5,KAP[S,KINTKK.
KIN TCI, "SIMIS.KIMDP.KAXIU.NA.NARI A.NC.NDA,
WlK>NN,NM«Ul,MltllS,Nf]TRr,NdTHC2,NOTHK,
IJI!?kl,NI'\/kTl,N[)VKT?,N()VKT31Nl,f)NCE.OPIM,
dPhH.OVPAYI.dVKIM.PAYLHR.PFRUN.PNONU.PNDSIG,
I'RHI I r,UO,01.02,01,0*.05,06,07,08.09,010.
01 1 , OH AX, 00, Oil I AVF,CO I MAX,OUI WIN,OUISIO,
OIJllMC,UUItlM,OUI2,«,RGVMAX,RGVMIN,RIGKA
(IKPdN //!()/ K I(,KH,K II, MAX, « IGVtL .RKA,RKAA,RKB,RKBH,RKCC,
K('AUI',,HMXDSR,KMxnSIlRNU,RUNNU,SCOLHL,SMWRKT,
'-.KK.Ml.STAT.SIMrsT.STRFML.SUMHUT.SUMrRK,
IAwfA,fHALDi.TlHF,TIPEO»TNF-TYP,TNGHUN»
HINAGf , Kilf.riS, TO I TON,TOTUT,TRC, TRCSIN.TRES,
II' H(25) , ANOHUNI251 , ANC)RUT(25)
ASNI!lM(25),AASSUN(;>5l,AXll25l .AX2I25)
AYII/^I .AY2I25I, R(10),CCL(6),CULMLKI*)
CORArHi*) ,(15(6) .EVFMI60) ,HISC12(16)
MIS(. I >l 1ft I ,MI',(, 1*1 16),HISC22( 16) .H ISC 23 I 161
HIS (.,>*( 16) ,HISf )?( 16) ,HISC J3I 16) ,H ISC 3*1 161
Ml '.( 'i? I 16 I ,H ISC* 31 161 , HI SC**( 16) ,111 STR1 I 161
H I S I U 1 I I (. ) , H I S TU ? I 16 I , H I S T LI 3 I 16 I , H I S IU* I 16 I
IIIMM(60I ,f)VRIMI50) ,PERUN(*) ,00(501
(JtJI IMCU>0),OUI2I 300),RaARIS(25l,STAT(90)
DICI NMCN IIMK60) ,TdNAr,M6) .TOTWTISOI .TRCI601 .TRIPI901
TKKLDI50I .TRLI60I ,TSIMI 1000 I,WAIF(50 I
lrlMLI2,12), OUJrrM(50,6), RKAA(*,2),
RKHIt(4,2>, KKCCI *,2),TAHEA(50t 31 .THALOSI 50i3l,
I IT 01 2, 12 I i TNF TYPI 50i 31 t TNQHUNI50,3)
CAI I IDCI-FKI IONU)
lll=IKANK
ccr: = 0
IF I 11(1 '10,40,91
90 P(,f,= l
IK--IR
91 II Iflini 100,100,101
100 IXX; IDNII+IR
K i ir.UHf I IXX )
(,( K) 10?
101 I»X« IDNC* IK
XK -r DRI (IXX I
10? <,/UL IINI'ACKI (OWN, IFIRSTtl ASF )
I 1 ASI
II II I 10 t, 10 ), 10*
103 fAII PACM inwN.IDNUilDNO)
|XX= IDNlit II'
K PKI (IXX 1=0
105 III IUHN
10'. 1 1 ( M ( I n ) 1 0 ft , 1 0 6 , I ? 2
106 |XX^L»IK
IflKOKM I XX)-K) 107, 107, 108
12? IXX=I « IH
ir iroRt i ixx I-XK) io7,io7,io8
10( TAIL F [LAST! IDNQ, IP, inWN)
l,r I(J 10")
10H JSUC=I
IXX^I • IP
TAIL IJNPACKI ICOREI IXX1.JP.JS)
L'JP
11* 11111115,115,116
115 CAIL F II F SII IONO, IP, IOWN4
01, ru 105
116 l!(*u!)> 119,119,120
119 IXX = I « III
IMK.OKtl 1XXI-KI 121, 121, 108
1^0 IXX-L'IR
IMLIIKII IXXl-XK) 121,121,108
1?1 1XX= IOM >IP
fALI PA( Kl IC.ORL I IXX I.L.JSUC)
I X X = L • I P
(.ALL DNI'AC.KI ICIJHf ( IXXl.JP.JS)
TAIL PACKI ICdRF ( IXX I.JP.IDNO)
ixx= isur • IP
CAIL UNPACK! ICCIPf I IXX liJPiJS)
CALL PACM IUIREI IXX I.IDNU.JS)
G( K) IG5
FNC
0? 10 UK
0280 FLR
0290 FLR
0100 FLR
0310 FIR
o)?o FLR
0330 FIR
01*0 FLR
0350 FLR
0360 FLR
03/0 FLR
03BO FLR
0390 FLR
0«00 FLR
0410 FLR
0
-------
(,
(
(
c
c
804
1 C.U 1 V A| 1 Nl 1 ( 1 (.DC 1 , MlH 1 >
1 \lffllH AM; lilKINSII'N F(]R SIMULATION
( (IfMUN /III)/ A'), ACRE , AHAI US , ANF TYP, ANOHIJN, ANORIJF , ASNUPT t
1 AASMIN.ASSSIIN.A', SUNK,AXI,AX2,AYI,AY?,n,CCL,rLKTM,
> C()IH)F,(UIHI<,C(IIMlK,COlTM/,CnMPAP.CUNA,tONB,
) fUNC , (.ONDtC (iNF ,( IINF , CD SCIIL . LOR A r.K , CHSI NT),
4 (.RLWIS,(RU'W,CSHRK. ,C.SIMR,(, TS, DAYS, DEI DF.P.IJMTAVE,
S IIMTMAX.IIMTMIN.IIMTSIf. , DFjLCm ,I)OLP IG, DDL TON,
6 Dill ! S,l,RUPAYtl)RUVI
'(.FMIIM /HI)/ Ml', III ] ,l Nl/li , NN.NIIRIH .NO! 1- I S, NO IRC, NO IRC, ^, NO IRK,
S NMPl ,'lfWKT 1 ,NIWKT2,NUVR1 3,NT , ONCE , OP I M,
/, rm»l'.IIVI'AYL,UVRIM,PAYlHk,PrRUN,PNDMU,PNUSlG.
/ PMh(lI(jOUlU2CHU4U5U6U70f)Q9UiO
H Ull.rjMAX.OQiUDIAVr.CIJIMAXiOUIMI N.UUI SIG,
9 LUITMf .UUITlM.IJUTZ.R.RGVMAX.RGVMINtRIGKA
C 111" Ml IN /I' I;/ RI',KH,Rlf,MAX,R|f,VFI ,RKA,RKAA,RKB,RKF»H,RKCC,
1 HtlADIStRMXDSR.RMXIISI , R Nl) , RUNNI1 , SCI1L ML , SMHRK1 ,
? 'jV. 1 (,ML . MAT , SI Ml ', I .SIRFUL, SUMRUI , SUM IRK ,
! IARIA,IHALIJStTI)'l,Tir'(titTNFIYP>TNOHIJN.
I25).ANHYPI25) , ANOHUNI 2? 1 , ANORUTI 2M .
1 ASNUPT 1 2'il , AASSUNI25 1 ,AX1 1251 .AX2I25I .
2 AY1IPSI ,AY2(2')I, HI 10) ,CCl 161 ,COLMl Kl/4 IX, I'lHS IMULAT ION RUN I3.37HSHOKS THE RESIDENTIAL ARFAS D 1 V I SI ONS0690FNLP
C
806
6/4 IX .55HANI) THIS DISPOSAL SITE. THE RUN HAS SIMULATED ONE HEFKS
7/41X,42ITPI RAT ION AND THE RFSULIS ARF SHOWN BELOW.)
1 t IIRMAT ( ll'l / 111-/ 1H-,
1 41>X,I>OMIN IMIS RUN THFRH IS A TRANSFER STATION WHERE THE
?/'.lX .SSHt lllLFf T ION TRUCKS HRING THEIR LOADS. THE SOLID WASTE IS
)/4 IX, 14HIRANSI FRRf U TO 14,3711 CUBIC YARD TRAHERS AND CARRIED
4M1X, SMITH! SF TRAILERS PULLtD HY TRACTORS TIJ THE FINAL DISPOSAL
•>/,F7.0,31H THE TRANSFER STATION IS AT CO-0810FNLP
9/
-------
111 I), '. I X,', ',11 I.
t \ \ 0 t 40X ( 4 '(MM .
HI I), 4 (IX, 44H'I.
'.Ill), 'IX ,4'iHIO.
'j II'I/II /IH-/1H
ft in
/inn
HII
9|l'0
I II
I IIKMAT I
Iinr, cix, 14H14.
?IH , l'IX,4'>H
IMIIIAMS I'l H KIN K1U INIIRE WHKS WORK ...,F1|.2/
tnillCMIIN tHUI.K TRAIFIC MIIFAt.l- Fll.l/
11111 n r IIIN i RUCK NF ir.HisiiRHUim MILEAGF ...,ni.i/
TMAIlfR IRAI.FOR TRAFFIC MILFA(,E , Fll.l/
, VIX.l^Hll. M/MHI R [IF UlllFCrillN TRUCKS GETTING/
UNt HIIIIK (If IIVERIIMF DURING WEEK ,I6/
NUMHtR lit ((/(LECTION imiCK', GfttlHG /
TWII HOURS OF OVERTIME DURING WEFK ,I6/
NIIMHFR llf TRUCKS GET TIM, MOKF THAN /
fWO HflURS OF OVERTIMF DURINf, WtEK ,161
)'»X, I 3H
I'lX.^OH
1 ') X . ,> 1 H U
'. It'O,
'•II' ,
7li'n,
H it' ,
•ill* ,
I II'O,
4 in
•>1H
6 I HO
an
B064 FORMAT!
1 int), 39X.30H21.
?1HO, )9X,IflH??.
un , 42x,4mi
4IH , 42X.40H
C
B065 F
THERE WERE,I4,2<)H BREAKDOWNS OR FIAT TIRES ON/
COLLFCIION TRUCKS DURING THE WEEK. /
THE COLLECTION TRUCKS MADE,16,1)H TRIPS DURING/
THE WEEK./
THE TRAILER TRACTOR RIGS MAOf,lft, 6H TRIPS/
DURING IHF WEEK./
AVF SIG MAX MIN /
TIME IN MINUTES /
IN OISPOSAl , 4F6.Z/
PERCENT TIMl SPENT BY COLLECTION TRUCKS /
IN CriLI FCTING...,F9.1/
IN TRAFFIC ,E4. I/
IN DISPOSAI ,F9.1/
OFF ROUTE ,F9.I/
AVE SIG MAX MIN /
HOURS IN WORKDAY ,4F6.1)
1020FNLP
10 IDFNLP
1040FNLP
10->OFNLP
lO'.'ll Nl P
1070FNLP
10HOENLP
1090FNIP
I IOOFNIP
IIIOFNLP
1120FNLP
1 I 1
-------
1 I ri lll> , 1 I' I I IK , I SHU ,UKHM ,UUI AVt , UUISIG.Ut.il M kX.UUIMIN
If ( AV.MlN.NI .1.1 (',() Id ltd?
Ul> I II I I I II, III I I
66? M I ASSMJN.I U.O. ) GO TO 7/7
I'l 4(ll NIP
1940FNIP
HH I I I I II U, I10H1 I I IMFOI
I I IMFUI
T IMtOI
TIMFUl
,11, I IP,FQ(2.1). 1IWEO< 1,21 ,TIMEOI2,2).
,3>,TIMFa<2,JI.TIMFOIl,<.),TlMFO<2,<.),
.%).1IMf.Q(2,!}),TIMf 0(1,61, T IMFOI 2, 61,
,7l,TIMrOt2,7lfTIMEU(l,8), T IMF 01 2,8) ,
, '(}, 1 IMFU(2,')I .TIMFQI 1,101 ,IIHFU(2, 101 ,
,U),TlMFOI2,ll>.TlMEOIl,12>,TlMfO|2.12>
HU 1 U ( 1 1 n
nlPFNSIHN REQUIRFU IN THIS ROUTINE ONLY
1)1 PI NSI liN XX I 6 I
in i.r >(02 i * i,is
X X | 1 I i ((111) « C I S ( I I
902 MM INIIf
II I ASSSIIN.Nt .0. I r,0 10 500
HH I I I I II.U, SO?)
500 nil I II I II 11, HO',5 I HJNAOF.I 1 I.XXI 1 ) ,TONAGFI2I ,XX(2),
1 KlNAGF I 3) ,XXI 3 I .TONAGFCi) , XXI4 I ,
2 UINAGF ( 5 I, XX I'j I , TONAC.F I 6 I , XX ( 6 I
M i ns'iMm.i u.o. i no in 778
Ml' I II I lOIJ.HObA )
IK! 13 I - M.90
IHTKIPIll.FU.O.) GO TO 34
3 ) (DM INIIF
) J « 71. JJKK
.177 = TRIP(J)
Mkllt I IOIJ4H067) J, J77
45 MINT INUI
HR ITU 1UU,B06B>
DC 531 1 •= 51, NOTRC2
.178 - IKIPI I )
MH 1 III IUU,8p69I I.J78
331 rcMlNUF
P P 1 - I) I 1 )
PP? = HI 21
P P i - I! ( 3 I
1<)(,OFNLP
1970FNLP
19801 NLP
1990f NIP
?OOOTNLP
201 OF NLP
2020FNLP
2030FNLP
20'.0f NLP
2050FNLP
2060FNLP
2070FNLP
?OHOrNLP
?0')t)FNl_P
2100FNLP
2110FNLP
2120FNLP
2130FNLP
21AOFNLP
2150FNLP
21ftO' NLP
2170FNLP
2190FNLP
2200FNLP
2210FNLP
2??orNl P
2250FNLP
22-.OFNLP
2250FNLP
2260FNLP
2?70FNLP
22HOFNLP
2290FNIP
2300FNLP
2110FNLP
23JOFNLP
2330FNLP
23<.OFNLP
2350F NLP
2360FNLP
2370FNLP
23HOFNLP
2390FNLP
2<.OOFNLP
?'.10FNLP
«F FUHN
I Mi;
2MOFNLP
2*'iOFNLP
2450FNLP
illiflC HISI«
MJHHIIUUNF HIS1Ut.RND.YY)
I) I PI Nil CN X(?0
N=/7 I II
/N"N
NN *N» I
YP IN^ZZ 121
YPAX-// I 3)
IU! 'lOOl 1=1, N
DO 4002 I -- UNN
/ I =1
AOO? Y( H--YMlN»lll-UO>«OELY
XI 1 1=71 1 I
ur, AOOY<[)«(DrLYMKNl>-Xlt-l)>/{lll>
4008 HelUKN
0010 HST
0020 HSI
0030 HST
00<,0 HST
0050 HST
0060 HST
0070 HST
OOBO HST
0090 HST
0100 HST
0110 HST
0120 HST
0130 HST
0140 HST
0150 HST
0160 HST
0170 HST
0180 HST
0190 HST
0200 HST
0210 HSI
0220 HST
0230 HST
•IBFTC ICCH.
SIJI'RDUTINF IDCHEK(ILNO)
C
COPPON AND DIPENS10N FOR LIST PROCESSING ROUTINES
CCPPUN ICIJf, .ICALDR.ICHECK.ICLOCK, I CORE . I DUPiM2. 1 DUPM4 , I FR5T 2
CCPMI1N IFRSI<,,1FRSTB,|I)VRHO,IUPE1,1TIMF2,ITYPF2,JBUG.JCHFCK
COPPON PAXCRE.MAXINT.MAXT.ITYPEI
DIPINSIIN I CORE I 1000), CUREI50)
I I ir.UHF .CORE I
0010IOCK
00201DCK
0030IOCK
0040IDCK
0050IOCK
0060IDCK
0070IOCK
OOB010CK
0090IDCK
0100IDCK
OUOIDCK
0120IDCK
-------
C,( MMllN AM)
f r,S lljtv FIJK SIMIJIAIKIN
COMMON /Ml;/ A'),M llh.AHALDS, ANt- T YP, ANntHJN , ANIIRUT .ASNUPT,
1 AflSSiJN,ASSSUN,ASSUNK,Axl,AX?,AYI.AY?,fl,CCL,CLKTM1
2 C(Jl f RF ,C(JLHK,UII Ml K.CUL IK/ ,COMPAP,CONA,CONB,
3 CONl .COND.CIiNF .tr.MF.COSCOL.CORACR.COSlNn.
TUltHISTU?lHlsru3lHISTU4.
1 KOI FR, |Nf INCKMI i lnu> IRUNNRt ITIMLi JOH> JTRCt
2 JIRL, JIRPCL ,JTRHHr,,K,K2,K'i,K5,KAPTS,KINTRK,
3 K INIRL.KSIMF S , K TMOP , t"AXL OtNA ,NAR E A , NC iNDA ,
TS,NnTRCtNf)TRC?.NOrH»l,
A URHM.nvPAYL ,(IVR I M , PAYLHR , PEKUN, PNDHUi PNDS I Gt
1 PRHrLT,aO,01,OZ,U3,a«t01'.06,07,08,(J9,010,
II 01 1 ,OMAX,OOiQU! AVE , OU I MAX , QU I MI Ni UU I SIG,
S OU1 IMC, gull TM.UUT?,R,RGVMAX,R&VM!N,RIGKA
COPMIIN /HO/ Rtr,KH,HtGMAX,Rir,VFl,RKA,RKAA,RKR,KKBH,RKCCt
1 RnAUIS.RMXDSR.RMXDSTtRND.RUNNn.SCULMl.SMWRKT,
) SR IGML , SIAT.i.rMFST.SIRFML.SUMRUT.SUMrRK.
3 TARfA, IHAlDSt T IMF, T IKFO. INEI YP, TNOHUN,
>, TtlNAGF, rdFCOS, H)TTUN,T[)rwr,TRC,r«CSIN,TReS.
5 1KFHK, tKfUL , JHf !Ml, TR IP, TRKOAY, FRKLD, TRL,
h TRLHAL.rRPCOL, TR PR 1C , TRPTM , I SCOST , TSHR ,
7 TSLBPS, rSTM,TX,TY,UNACRE,UTILTY,VELMAX,
H VFLW1N, VtLMUKtVf LMUT,VELSGR, VELSGT.HAIE ,
q MAIE7,HT,XOAY,YRS
OlfFNSlON AHALDS(?5).ANfcTYP(25).ANOHUNI25) .ANORUTI25).
1 ASNUPTI25I .AASSUNI25) ,AX1 (25) .AX2I25I .
1 AYK25) .AY2I25I, H ( 10 ) ,CCL ( 6 I .CQLMLK ( 4 ) ,
3 CURACRCi) ,CTS(6) ,EVENT(60) ,HISC12(16I,
4 H1SC13I Ifc) .H1SC1AI 16I,HISC22( 161 ,HISC23( 16) ,
5 H[SC2<.(16I,HISC32< 16I.HISC33I 16I.HISC34I 161,
6 H1SC<.2( 16 ) ,HISCIOVRHD,ITIMElfITIHE2i I T YPE2 , JBUG, JCHECK
CUKMIIN MAXCRf,MAXlNT,MAXI,ITYPEl
ICUREI1000), COKFI50)
COCftJN AND DIMENSION FOK SIMULATION
CnfMON /BD/ A<),ACRE,AHALOS,ANETYP,ANOHUN,ANORUT,ASNUPTf
1 AASSUN,ASSSUN,ASSUNK,AXl,AX2,AYl,AY2,B,CCLtClKTM,
2 CnLFRE,CULHR,CniMLK,CnLTMZ,COMPAP,CaNA,CONB,
1 CONC,CUND,CGNE,CONF,COSCOL,CORACR,CQSLNO,
<, CREWTS,CRUSZ,CShRTC,CSTHR,CTS,DAYS,OEll)EP,OMTAVE,
5 OMTMAX,DMTM1N,UMTSIG,DOLCOL,DOLRIG,DOLTON,
6 DOLTS.OROPAY,OROVRT,OSLC,DH,EVENr.FlNOAY,
7 FLATNO,FLTLIM,FX,FY,H1SC12,H1SC13,HISC1*,
8 HlSCZ2,HISC23,HISC2 NDR,NN,NORUT,NOFLTS,NOTRC,NOTRC2,NOTRK,
5 NOTRI,N(WRT1,NOVRT2,NOVRT3,NT,C1NCE,OPTM,
6 ORHR,aVPAYL,OVRTM,PAYL8R,PERUN,PNOMU,PNDSIG,
7 PRbFLT, 00, Oli 02,03,0*. 05, 06, 07,08,0'), 010,
B UU,UMAX,CO,UUlAvE,CUlMAX,UUIMIN,aUISIG,
1 (;UITMC,QUITIM,flU!2,R,RGVMAX,RGVM|NIRir.KA
CCfMUN /I'D/ K IdKB.R ICMAX,R lr,VEl ,RKA,RKAAIRKB,RKHB,RKCC,
0010 INI
0020 INI
0030 INI
0040 INI
0050 INI
0060 INI
0070 INI
OOBO INI
0090 INI
0100 INI
0110 INI
0120 INI
0130 INI
0140 INI
0150 INI
0160 INI
0170 INI
0180 INI
0190 INI
0200 INI
0210 INI
0220 INI
0230 INI
0240 INI
0250 INI
0260 INI
0270 INI
0280 INI
0290 INI
0300 INI
0310 INI
0320 INI
0330 INI
0140 INI
-------
HI) All 1 S,«MXI)SH,RMXI)S1 , HN1-), HDNNl) , SUH ML .SMHKKT ,
SRH.MLtiI»T,STMfS I.SIRFMLiMJMRUI.SUMTRK,
IAHIA,THAll)S,TIK[,II*Eg.,TNtlYP, INdHUN,
IRfHK,THFMl,IKFIf/,IKlP,[RKUAY,IRKLl),IRI,
111 PI NS I( N
(HCINSION
ISIHPA,TSTMttX,TY,UNACRF,UtlLTY,VtLMAX,
VELMIN.VFLMUR.VflMUI.VF-L'iOR.VELSI. t.WATE,
WAIF./ ,Kt , XOAY.YRS
AHALI)S(/"i],ANETYPI25> . ANIJHUNI 25),ANORUU25).
ASNUPI ( 25) , AASSUNI25) .AXK25I ,AX2t2M ,
AYU25) .AY2I25I, B( 10) ,CCL (61 .COLMLKUI .
UJRAt.KI',1 .C1M6I ,FVtNI(60l ,H I SC 1 2 ( 1 6 ) ,
HISf. 1)1 161 , HlSCl'. I 161 , H1SC22I 161 ,HI SC23< 16) •
HISC2M161.H I SC 32(161, HI SC 33(161, HI SC34I16),
HI';C , RKAAC.,2),
1 RKI)8C.i2), RKCCU.2I ,TARf A(50, 3) , THALDS ( 50 , 3 ) ,
1,12
I T IML ( I , J ) J 0
H63 « NlINdF
86 i 0
rvrNH i i - o
33 CFlMINUt
ACHC « 0
CLKTM - 0
COLIMZ - 0
IJCPTM; • o
FIN I) AY " 0.
IOVRIM • 0
K i - o.
11IWK1M •
uic • o
S I A It) «
ri I -o
1 1 12 -o
WT - 0
Kf IUHN
I M,
01V) IN 1
0360 INI
0370 INI
OiHO INI
O3')0 INI
0
-------
(I.MMIIN AM, UIMINSIIJN Flip SIMlltATlUN
I < MHI1N /III)/ A'J, AC Hf , A HA I DS.ANF I VP , ANDHUN i ANURU t .ASNUPT ,
I A»SSIIN,ASSSUN,ASSUNK,AX1,AX2.AYI,AY2,B,CCL,CLKTM,
fllNC .CriMJ.ClINC ,CI)NF .COSLUL .CURACR.COSLNO,
(,RlwrS,CRUS/,C SHRir.CSTHR, CIS. DAYS, DFLDEP.OMTAVF,
l)MTMAX,l;MTM|N,()M SIG.DOLCOL.OOLRIG.OOLTON,
Dili rs.DRUPAY.DRLiVRI ,OSLC , OW , f VFN T , F I NDAY,
HAIfJI),KHr«,FX,FV,HISC12,HISC13.HISC14,
HIS122,HI5C2I,HISC ?4,HISC»2,HISC33,H1SC34,
HISC42,HI SC4J.HI SC44
COMMON /HI!/ HISIIH .HISIUl ,HISTU2,HISIU3,HISTU4,
ICniFH, IN, INLKMT, inu, IRUNNU, I TIML, JOW.JTRC.
JIHI .JfRPCl , jrRI'Rr,,K,K2,K4,K5,KAPTS,KINTRK,
KINIRI ,KSTMF S.MMUP.M AXL 0 ,NA ,NARE A, NC ,NDA,
NDR.NN.NORHT.NUH I S , NOTRC ,NOTRC2 , NO I RK ,
N01KL ,NOVRT I , NOVRT2.NOVRT 1, NT, ONCE .CJPTM,
ORHR.OVPAYL ,I)VR IM , PA YLHR , PERUN , PNDMU , PNOS I G,
P«HI( f, (JO, 01 ,«<•. 03, 04, OS, 06, 07, OB, 09, 010,
Ul 1 .OMAX.QU.UUI AVF , OUIMAX.OUIMIN.OUlSir,,
UUI TMt ,CIJI I IM.QUT 2 , H , RGVMAX , HOVH I N, R IGKA
CllfMON /111)/ KIOKH,R IGMAX.R If.VEl ,RKA , RKAA ,RKB , RKBH ,RKCC ,
Rf)A|)| S.KMXOiH.RfXDSI , RND , RUNNO , SCIIL ML , SMWRK T ,
SRIGMI ,r,TAT,STMFST,srRFMLf SUMRUr.SUMTRK,
TAKIA.THAIOS.I IHF,T[HEg,TNEIVP,INOHUN,
rnNAGE,iiiTCiis,icrrON,rorwr,rRC,TRCsiN,rRES,
TRFHR,TR>-ML,TKF1M/,rRIP,TRKDAYlrRKLD,TRl,
TRlHAI,rpPC(U,TI(PRlr, .TRPTH.TSCOSr.TSHR,
rSLRPA,TSrM,IX,rY,UNACRF,UTILTY,VELMAX,
VELMlN,VFLMlm,VELMur,VELS'5R,VEl.SGT,MATf,
WAT( 7,HTtXUAY,YRS
AHALI)r, l2">|,ANErYPI25) , ANOHUN(2i) , ANORUTI25) ,
ASNUPI (251 ,AASSUN(?i) .AX1I25I ,AX2(25t ,
AYK25I ,AY2(2'.)I B ( 10 I . CCL ( 6 I .COLMLK I 4 I ,
CORACRIAl ,CrS(6l .EVENTI60) ,HISC12(16),
HISC11(1A),H1SC1A(16I,HISC22(16),HISC23(16I,
HI5C24I 16I.HISC32I 16I.HISC33I 1 61 .HI SC34I 16> ,
HI5C<,?ll6),HIbC<,M16),HISC,MISTU?(16l,HISTU3ll6),HISTU<.U6),
IJPTMI60) .UVRIMISO) .PERUNCil ,00(50) ,
QUI I MCI 60) ,01)1? I )00),ROA[)ISI25),STAT(90)
DIMENSION TIr"l (601 ,niNAGI(6l ,rurHT(50) .TRCIfcO) .IR1PI90I
TRKLIJ(SO) ,TRL(60I , I STM ( 1 000 1 , HATE I 50 I ,
OAYSI2,3I, lllfL(2,12), OUI T TM ( 50, 6 I , RKAAC.,2),
RKnl)C.,2), RKCCIA.2) , TARE A ( "SO , 3 I , THALOS I 50, 3 I ,
« TIMEO(2»12). INf IYP( 50,3) , TNOHUN(50,3)
IMORU°I 1'MAXINf*! 2
Rl TURN
FNC.
01 JO
0140
0150
0160
01 70
0180
0190
0200
0210
0220
0230
02*0
0250
0260
0270
0280
0290
0300
0310
0120
0)30
03*0
0350
0360
0370
0380
0390
0400
0410
0420
0430
04 '.0
0450
0460
0470
0480
0490
0500
0510
0520
0530
0540
0550
0560
0570
05HO
0590
0600
0610
0620
0630
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
PAK
»IBFTC
C
C
C
SUBROUTINE PANIC
COMMON «NC DIMENSION FOR LIST PROCESSING ROUTINES
COMMON I BUG,ICALDR,[CHECK,1C LOCK,I CORE,IDUMM2.IDUMM4,IFRST2
COMMON IFRST4,IFRST8,IUVRHD,ITIME1,ITIME2,ITYPE2,JBUG,JCHECK
COMMON MAXCRF.MAX INT,MAXI,I TYPE 1
DIMENSION ILUREUOOO), CORt(50)
ECUIVALENCLIICORF.CORE)
COMMON AND DIMENSION FUR SIMULATION
COMMON /HO/ A9,ACRE,AHALDS,ANFTYP,ANQHUN,ANDRUI,ASNUPT,
I AASStJN,ASSSUN,ASSUNK,AXl,AX2,AYl.AY2,B,CCL,ClKTN,
? COLFRf ,U)LHR,COIMLK,COLTMZ,COMPAP,CIINA,CUN8,
3 CONC.COND.CONE.CONF.CCSCOL.CORAr.R.CnSLND,
4 CREW!S,CRUSZ,CSHRTC,CSTHR,CIS,DAYS,DELDEP,DMTAVE,
5 UMTMAX,DMTMlN,UMTSIG,OnLCOL,DuLRIG,OnLn)N.
6 Dr)L!S,L>RI)PAY,ORIJVRI,nSLC,OW,EVENT,HNOAY,
7 FLATNO,FLILTM,FX,FY,HISC12,HISC13,HISC14,
8 HISC22,HISC23,HISC24,HISC32,HISC33,H1SC34,
9 HISC42.HISC43.HISC44
COMMON /BH/ H1SID1,HISTU1,HJSTU2,HISTU3,HISTU4,
1 ICOLFR,IN,tNCRM!,Iau,IRUNNO,ITIM,L,JOH,JTRC,
2 JTRL.JTRPCl , JIRPRr,,K,K2,K4,K5,KAPTS,KINTRK,
1 K[NTRL,KSTMFS,KTMnP,MAXLO,NA,NAREA,NC,NDA,
4 NnR,NN,NOHUI,NaFLTS,NOIRC,NOTRC2,NOTRK,
5 NOTRL,NCVRTl,NOVRI2,NOVRT3,NT,aNCE,OPIM,
6 URHR.OVPAYL.UVHIM,PAYLBR.PtRUN,PNDMU,PNDSIG,
7 PRHFLT,CO.Ul.02,03,04,05,06,07,08,09,010,
H 011,UMAX,UO.OUIAVF,OLIIMAX,OU|MIN,gU[SIC,,
9 GUI IMC.UUIT !M,(jlJT2,R,RGVMAX,R&VMIN.R IGKA
C(.MMON /BO/ RlGKB,HIKHAX,HICVf L ,HKA,RKAA, RKB ,KKHH , RKCC ,
1 ROADIS,RMXDSR,RMXDSI,RND,RUNNO,SCnLML,SMWRKT,
2 SRlGML,SIAT,STMFST,SIRFML,SUMRUI,SUMrRK,
3 TAREA,THALOS,TIME,TIMEO,TNETYP,TNOHUN,
4 TONAr,F,TOTC(;S,Tr, TTON,TOTWT,TRC,TRCSIN,TPES,
0010 PAN
0020 PAN
0030 PAN
0040 PAN
0050 PAN
0060 PAN
0070 PAN
0080 PAN
0090 PAN
0100 PAN
OHO PAN
0120 PAN
0130 PAN
0140 PAN
0150 PAN
0160 PAN
0170 PAN
0180 PAN
0190 PAN
0200 PAN
0210 PAN
0220 PAN
0230 PAN
0240 PAN
0250 PAN
0260 PAN
0270 PAN
0280 PAN
0290 PAN
0300 PAN
0310 PAN
0320 PAN
0310 PAN
0340 PAN
0350 PAN
0360 PAN
0370 PAN
0380 PAN
0390 PAN
-------
>, !«MU',!l'(ML,IRFIt-'/,FHIP.IRK[)AY,TKKU).TRl,
6 1R| I' A I , 1 UPC I II , IK I'll If, , TRPIM, F SCO SI , I ilm,
I l5lHPA,TSTM1rx>:Y,IJNACRF,I.ITII_TY,VFl.M»Xt
fl VF|M|N,VfLHllR1VllMlJI,VFLlOKiVFl) ,AY2I25I, h( 101 .CCl ( 61 .C.OIMI K 14 I ,
3 (UHA(«I4I ,CI',(6) ,EVfNT(60) IHISC12I16I,
4 HI SI. M(16),HISC14(16),HISC22(16),HISC23I16),
5 HIM 2M 161 , HISC, 3?( 16 I , HISC )3( 16) ,HI SC34I 161 ,
6 HIM'. ,M16),HISr.4)(16),HISr<,4<16),HISTUltl6),
I MISIUI(16),HIStU2(16),HlS!U3(V6l,HISHI4(16),
H (IPIMI60) ,(IVRrM(50) ,PTRUN(4) ,UO(50) ,
•I UU I IMC 160 ) ,UI)I2 I )00) ,R(JAI)I il 25 I ,STAT I 90 I
DIFTNSKIN I1MFI60I ,I(INAG[(6) ,Tl)TWT(50) ,TRC(60) .TRIPI
I lHKLIi(50l •TKLIhO) , ISIMI 10001 ,HATF ( 50) .
! IIAYSI2.3), II[MI(2,12), UUIUM150,6), RKAAI4.2)!
i RKHI114,?), HKCLI 4, 21 ,TARF AI50, 31 , THALOS < 50 , 3 I ,
4 IIMtQ(2,12), FNMYP(50,3), 1NOHUN I 50 , 3 I
MR lit I IIJU, ICO)
WRlIi llfll,200) NI, ITlMf 2. 1 IYPE2
100 FTHMAI I lF(-,25HPANir, SUHROUTINfc tNTfRFD.)
200 FdUMAI I IFl-i 16HFOK FRUCK NUMIIFR.I3, BH T1MF
(HI
»IBFF( RAND"
SIJHRdUI INt RAN DOM IMF AN, S IGMA.X )
RTAL Mt AN
CAI I niNMRMI X,Y,0. )
X'CF AN> S If.MA'X
R[ FUKN
f MJ
,17, 9H EVENT «
Fir. V i f I *
MJIIRlllir INF KF MF r, I ( II, NO, I P, ION)
tllMMlIN ANU (JlMINSlUN FDK I [SI PHUCfSIINf. ROUTINES
(.fCHON I !»)(,, If. AI I)R, l(. HF I.K, IC1DCK, ICflRF, I DUMM2 , 10UMM4, IFRSI2
( ( FMIIN II f', F<,, IFRSIH, [(IVRHO, It IMF. 1, IT IMF-2, I I Y PI 2 , JF31K, , JCF(F CK
(I.MMIItJ MAX(CI ,M«XIN1,MAXI,[1YPF1
I.IKFNSlCN K HUM 101(,l, (,l,Rf(50)
H.III VALfcM F ( K.FIPF ,Cf:RI I
fCNMON ANI! IJlffcNSlnN FOR SIMULATION
tnfMUN /(ID/ AS,Ar.RCiAHAI 0 S , ANF T Y P , ANOHUN , ANORUT , ASNIJPT,
1 AASillN,ASSSUN,A'.SIINK,AXl,AX2,AYl,AY2,B,CCL.CLKTM,
2 C()Lr«F,CULHI',CnlMLK,CULTM7,COMPAPtCONA,C(JNB,
3 CflNCtCOND.CtINF , CONF , COSCOL , CORACH , CUSL NO ,
', CKF/WTS.tRUS/.CSHRICiCSlHR, CIS, DAYS, (jriUFP.IJMTAVE,
S OMlMAX,OMTMIN,nMTSIG,OOLCOL,OOLRIG,OULTON,
6 rmLIS,DRUPAY,l)RUVRT,DSLC,l)W,EVENr,FINUAY,
/ fLAINO,FLTlrM,fXtFY,HISC12,HISCntHISC14,
H HISf22,FllSC 23,Hlr>C24,HISC32,HIS(.33,FtlSC34,
') FUSC42.HISC'. 3.HISC44
CfJfMlIN /Mil/ HISTI11 ,lll STU1 ,111 SFU2.HI STU3.FU i I U4 ,
1 If.ni f R, IN, INCRMT , |OU, 1RIINNO, ITIMl ,JOM, JTRC,
2 JTRt.JTRPCL.JIRI'RO ,KIK2,K4,K5,KAPTS,KIN!RK1
3 KINFRI ,KSIMI S,K tMUP,PAXLO,NA,NAREA,Nf,,NOA,
4 NnK,NN,NURUt,NnurSiNntRC,NnTRC2,NUTRK,
5 NOIRI,NDVH11,N()VRI2,NOVRT3,NT .ONCE ,(JPIM,
6 ll«HH,(WPAYL ,OVRTM,PAYLBR,PLRUN,PN()MIJ,PNOSIG,
7 PR IH I I ,1.'0,U1. 02,03,04,05,06,07,09,09,010,
B t,H,UMAX,li(j,UUl/Wt-1OUlMAX,UUlMIN,(JUI')l&,
9 IjU I IM(. , LUI T lM,mjl2,R,Rr,VMAX,Rr,VMIN,R 1GKA
(.OK Ml IN /HI)/ R I(,KU,H K.MAX.II IGVtl. , RK A , RK A A , RK II , HK I1H , RKC(. ,
HO AD I '>,RMXUSR,KMxrjST , RNO, RUNNf), SCOt Ml .SMWRKT,
SHII.MI.SrAr.ilMFSI.SIRFML.SUMRUI.SUMIRK,
1A|(IA,IHA1|J'),I|MF,FIKLU,INMYP, INIJFIIJN,
KiNA (,F, II) ICDS, lllll ON.IOIHI.TRC ,IR(.SIN,1RF^,
IMIMH.IHFMI ,IRt I fl , TR IP, IRKOAY, IHKLU, TRl ,
OIKENSH'N
ISL II PA,TSIM,TX,IY,U NACRE, UTILTY.VILMAX,
VtLMIN.VElMUK.VFLMLI.VELSCR.VELSGr.WATE,
hATE/ ,MT , XDAY.YRS
AF-ALnS(25l,ANEFYFM25l , ANOHUNI25) , ANOKUT I 25 I ,
ASNUPT (25) .AASSUM25) ,AXH25) ,AX2(25) ,
AY1I25) ,AY2(25), B I 10 I ,CCL I 6 I ,CDL MLK I 4 I ,
CURACFU4I .CTM6I .EVFNTI60I ,HISC12(16I,
HISC13I16I,HISC14I16),HISC22(16),H1SC23(16),
HISC24I16),H1SCJ2(16),HISC33(16),HISC34I16),
HISTII1(16),H 1ST U 2(161, HIST II 3116), HISt 114 (161,
(1PTMI60) ,OVRFK(50I ,PFRUN(4) ,00(501 ,
0
-------
Llll IM< I / o > ,t,ul,M XJOl ,W(JAI)I SI 25 I , '.'A f (901
MMII6IJ) ,K,NA(iM6> ,101*1150) .TRCI60I ,rRIP(9C)
IKKIM50I ,THI(M)I , TSTMI 1000I.WATE!50I .
llAYSU.tl. I I IMI (?, 12) , 0111 TTMI 50,61 , RKAAI4.2I,
KHIIIII'..?). I-KCCI'.,,* > , TARrA(50, 3) .THAI IJSI50, 3).
TIMI
HIM, - If IKS!
IMIUNDI 150,150.151
150 Hf JIJIIN
151 l*X = ll>N(.MP
(.AIL UNPACK! ICORFI IXX ) , JP , I f I R S T I
II I HI ( IXX I = -1
IMIIIH'jl) 156,156,159
156 ITHN--0
(,P III 150
159 (All PACK! H.HN, IF [RSI, I ASI I
IXX- IFlRSr«IP
(All UNPACK! 1CCJRF! IXX ),JP,JS)
(.All rtCKI IC.tIRt < (XX I.O.JS)
f.C FU 150
O'>40 RHF
0550 RMF
0560 RMF
0570 RMF
0580 RMF
0590 RMF
0600 RMF
0610 RMF
0620 RMF
0630 RMF
060 RMF
0730 RMF
0740 RMF
0750 RMF
0760 WMF
MBFTC RFI, I f RS T2
CCPMDN lFRSI^,l'«'H,ITlMf2,[TYPt?,JBUG,JCHFCK
CDC^ON fAXC.RF,MAXINI,MAXT,IIYPI:l
DIFfNSION ICORM1000I, CIJRCI50)
[ CUIVALFNCK I CORF, CORE I
COPPtJN AND OlftNSION FOR SIMULATION
CdCMUN /HO/ A9.ACRF.AHAl DS , ANE T Y P , ANOHUN , ANORUT , A SNUP T ,
I AASSUN,ASSSUN,ASSUNK,AX1,AX2,AY1,AY2,B,CCL,CLKTM,
7 CflLf RF.CULHH.CIII KLK , COL TMZ ,COMPAP,CUNA , CONB,
) CDNt.Cn NO, CONF ,(.()NF,CnSCOl,CURACR,COSLNI),
A CRIWTS.CRUSZ.C'illRTC.C'iTHR, CIS, DAYS, OELOEP.OMTAVE,
5 OHTMAX.OMTMlN.nf T S I G , OULCOL , ROL R I G , OOL TON ,
6 DOLTS.ORDPAY.IJRfJVRT.DSLC.OH.EVENT.FINOAY,
7 fLATN()rFLTLTM,FX,FY,HISC12,HISC13,HISCl',,
H HISC22,HISC23,HI',C2'i,HlSC32,HISC33,HISC3'.,
9 H1SC<.2,HI SC'.S.IHSC'iA
COMMUN /BD/ HIST01,HISTUUHISTU2,HliTU3,HISTU«,
1 IC(H FR, IN, INCHMT, IOU, IRUNNO.I TIML.JDW.JTRC,
2 JTRL.JTRPCL , J TRPRC, K ,K2,K'i , K5,K APTS ,K I NTRK ,
1 KINrRL,KSTMFS,KTMOP,PAXLa,NA,NAREA,NC,NDA,
* NOR,NN,N(JRUT,NOFLTS,NDTRC,NnTRC?,NOTRK,
5 NniKL,NOVRri,NOVRT2,NOVRT3,NT,DNCE,[IPTM,
6 (JRHK.nvPAYL ,C!VRTM,PAYLHR,PERUN, PNDMU , PNDS I G ,
7 PR I) FLT, CO, Ul, 02, 03, 0
-------
53
n (i A'> i i 20i), 2cs. /oh
II WN'O
(,( II, 2CC
r Al L PACK! II'V-N, 1MRSI ,L/\SI )
IXX I AST .IP
CAII UNPACK | ICIIHH IXX I.JP.JSI
( M I PAf K I H URH I XX I , JP.OI
(,l Id 200
I Ml
G6HIJ KML
0690 KML
0700 KML
07)0 RML
0'20 RML
0730 HHL
07*0 RML
0750 RHL
0760 RML
I T( "I M(l»
Ml UK I HI I INI Xf MOVI ( I UNO, IP, 1 U UN )
(.ClPNflN AND nmNSI'N FOR LIST PROCESSING ROOTINFS
< CfMON ll'llf,, K Al I)H , ICHECK, ICI OCK , 1COHE , I OOMM2, I IHJMM* , IFR5T2
r CMMilN II RSI',, I I HSTH, IIJVKI'U, I I IME 1, I 1 IMF />, I TYPE2, JHUG, J CHECK
ClffllN f"X(l'l,MAXINT,MAXI,IIYPIl
nlKINSIIN ll.l.R! ( nOfll . CORfl'jOl
V CHI VM t N( I ( IfllHf .(.(IRE I
((("•UN »Ml lllf'ENSIIIN FOR SlflllAllON
(_( PH(]H /IK!/ A<), ACHf ,nHALOS,«N( T YP , ANHHUN , ANORUT tASNIJPT >
1 »ASSUN,ASSSUN,ASSUNK,AXl,AXZ,AYl,AYi,B,r,CL.CLKTM,
2 Cdl F Ht- i tlJLHKiLOl MlK.tUL IH; .CUMPAPiCONAiCONB,
1 f CjN( , r HMD iCI'Nf iCHNT, COS',DLif.llRACK.CGSLND,
<, CKtwTS.CHUS/iCSt-RTCiCSIHRiCTSiDAYSiUFlDtP.DMTAVEi
S DCTMAX.DMVMIN.OMISlf, ,()(JLtl)L tDOLR If. > DHL 'ON >
t, lifJLTStl)fl)PAY,DKfJVRT,nsLC,DW,FVENt,FINDAY,
7 FLA[N NCFHliNUVRll ,NOVHI2,NnVRn,UT ,ONCt tOPTMt
6 IIKHR,UVPAYLlI)VKIMlPAYLBRlPEKUNfPNDMUlPNOSIGf
7 pRiin i ,co,gi,Q?,m,Q',,o'i,u6,07,an,a9,Qio.
H 01liUMAX,CUiUII|AVCt(iUlMAXtOUlMlNiUUISIGt
9 (JUIIMC ,UUITIM,OUI2tR,ROVHAX,R&VMIN,RI(,KA
(.(IF'fllN /HI)/ Rll,KH,RIGHAX,RIGVlL,RKA,RK;AA,RKFitRKHF),RKCCt
I R()AI)IS,IIMXOSR,RMXOSF,RNI),RUNNO,'jr,()LMI_,SMWRKT,
/ SR|f,Ml.'jlAI,STMFSI,STRFH|,SUMRUti SUMTRK,
) lAHIA.IHALU', .TlfljTIPFUrtNtrYP, TNUFIUN,
i, l(]HA(;l,l(lTf(iS,IllF!UN,lnTHI,TRC,rRC> .AY2I25), R ( 10 ) ,CCL I 6) .CFJLMLK ( 4 ) ,
3 CMRACRI FIISC2'»(16),HISC32I16I,HISC33I16),H]SC3'-(16),
6 HlSC42<16>,HISCM(16I.HISC,ROADIS(25),STAT(90l
nlCCNSITN IlMlltOI ,TF)NAGbl6) ,TOTWT(50) ,TRC(60) ,TR1P(90)
1 IHKLDI50I .TRLI60I ,TSTH(10001,HATEI 501 ,
? OAYSI2.3), ITlHLI2,12li QUI TTFK50.6 I , RKAAl',,2).
3 RKHOCi,2), RKCC I
-------
I./HI PA( K I l> I.U1 I IXK ) , IP , I ',(>(. (
I XX-- I S(K > (('
(.«! I IINI'M KIM 0"l ( f XX I , Jl', IS I
(All ('«( K< II I1IU I IXX I , I I'Hn, JS I
l» x. HIM • IP
II ( HI I IXX ) ' 1
(,(, II] 10?
FM:
OH/11 HHII
OB tU KMIJ
ot*c) nun
0850 HMO
OHM) HMD
08 fO RMO
0880 HMD
0890 HMO
tllll l( RPf HI
suriKiiur INF RANMI RII ,NI
C UNKIIKM KAMjflM I' KtPU I«f I (IN OF FIRST N INTEGERS
OIPFNSICN 1(11
l:r H 1 = 1,N
H I f I I -I
(,f 20 |»I,N
NN -->N- I t 1
J'=FII)AI(NNI"HNM(IOI«FL')AU I I
K=l I I I
I II I'll J)
?n i. u)>K
Kl IIJHN
FM:
0010 PPR
0020 DPR
00)0 RPR
00*10 RPR
0050 RPR
0060 RPR
0070 RPR
0080 RPR
0090 RPR
0100 RPR
0110 RPR
0120 RPR
0130 RPR
OlICHtCKrir. LOCKflCUREi IDUMM2, ll)UMM ,TRC(60) ,tRIPI90l
TRKLD(bO) ,m<60) , T S IM( 1000 1 , WA IE ( 50) ,
UAYSI2.3I, ITIKL(2,12), OUI I TMI 50, 6 ) , RKAAC.,2),
RKPD«i,2l, HKCC («,2) , TARFAI 50,3 I , THALUSI 50, 3) ,
IIMfUI2,12), INtTYP(50,3) , INOHUNI 50, 3 I
FMPENSICN TUTI60.6I
IF IXYXZ .EO.-218. IGQ TO 201
XYX7 = -2«8
CO 210 I = 1,60
rr 211 j = 1,6
TLTI 1 , J I = 0.0
0010 RGB
0020 RGB
0030 RGB
0040 RGB
0050 RGB
0060 RGB
0070 RGB
0080 RGB
0090 RGB
0100 RGB
0110 RGB
0120 RGB
0130 RGB
0140 RGB
0150 RGB
0160 RGB
0170 RGB
0180 RGB
0190 RGB
0200 RGB
0210 RGB
0220 RGB
0230 RGB
02*0 RGB
0250 RGB
0260 RGB
0270 RGB
0280 RGB
0290 RGB
0300 RGB
0310 RGB
0320 RGB
0330 RGB
03*0 RGB
0350 RGB
0360 RGB
0370 RGB
0380 RGB
0390 RGB
0*00 RGB
0*10 RGB
0*20 RGB
0*30 RGB
0**0 RGB
0*50 RGB
0*60 RGB
0*70 RGB
0*BO RGB
0*90 RGB
0500 RGB
0510 RGD
0520 RGB
05JO KGB
05*0 RGB
0550 RGB
0560 RGB
0570 RGB
0580 RGB
0590 RGB
0600 RGB
0610 RGB
0620 RGB
O630 RGB
06*0 KGB
0650 RGB
0660 KGB
-------
55
211 MM INllI
210 ( I1M I Nil I
?f)l I IMJAY - fl.
If (JDW.Nl . 1 I GU 10 H
B KMAK •= I IMI (NT ) « .5
.ITRC*TKC INI>«.5
STA|IJIKC) * 8
JT HI»IRI INI )t.5
ST Al I.ITKL I » 10
t,U 1 TMC I IIRC I « KBAK
X I 01 - IMJI TM(.I JTRC I - 08
XI 1 I ' XIOI/60.
IF 1X101.I F.480.) GO TO 100
WR ITLI I 111). 1 10) JTKC.X11 I
110 IOUM/ITI1H ,7HTKACTnH, I6.29H IS ON OVERTIME HAVING WORKED,F8.2,
1 6H HOURS)
XI 1 I = X I 11 - 8.0
M3 = X11 1 • 1.0
IF IM ».(,! .31 M3 = 3
If i - M 3
IF IYM3.ro. TrjTIJTKC.JDW) ) GO TO 100
IF IM). 1,1.2) GO TO 803
f,r 10 I HO 1,802), M3
rrTijiRi..)UM) = I.
l)( 1 ) - Ml 1 I • 1.
(,(. TO IOC
II I HITI JIKC.jnwI.FU.1. I Gil TO 220
If IIJTKC.JUMI » 2.
11(21 i BI2I » 1.
(,f TO 1(10
III I I • Ull) - 1.
T( I I JIHdJDW) » 2.
Ill 2 I " 111 2 I » 1 .
GC TU 100
IF I TOT (JTKf.,jnw).EU.l-) GO TO 230
IF I TOT IJTRC.JUHI.EQ.2.) GO TO 240
801
802
220
803
231
210
240
TTTIJTRC,JUKI
11 < 31 « BID «
r,n TO 100
Hill = fid) - 1
GO TO 2il
II < 2 I • H I 2 ) - 1.
Gf TO 231
3.
1.
C
c
c
c
100
10
20
35
30
50
99
DO 10 1 = 71,90
IT ISTATI ll.FOU?. 1 GO TO 20
COM INUF
r,r TO 50
DC 3"> J > 51, NOTHC2
IF ISTAT 1 J).E0.8. ) GO TO 30
CCMINUE
Gf] TO 50
NT " J
IVFNTINT) « 7
T 1 PI 1 NT 1 - KHAK » 10
TRt INT ) * \
TRCINTI . J
ST «T INI I - 9
Sf AT 1 1 I - 11
GO TO 99
F INDAY-99.
Rl TURN
[NO
0 h 1U KGB
OhHf) HOB
0690 RGB
OPOO RGB
0710 KGB
0720 RGB
0710 RGB
0740 RGB
0750 RGB
0760 KGB
0770 RGB
0780 RGB
0790 RGB
0800 RGB
0810 RGB
0820 RGB
0830 «GB
0840 RGB
0850 RGB
0860 RGB
OH70 RGB
0880 RGB
0890 RGB
0900 RGB
0910 RGB
0920 KGB
0930 HGB
0940 RGB
0950 RGB
09fcO RGB
0970 KGB
0980 RGB
0990 KGB
1000 RGB
1010 RGB
1020 RGB
1030 RGB
1040 RGB
1050 RGB
1060 RGB
1070 RGB
1080 RGB
1090 RGB
1100 RGB
1110 RGB
1120 RGB
1130 RGB
1140 RGB
1150 RGB
1160 RGB
1170 RGB
HBO RGB
1190 RGB
1200 RGB
1210 RGB
1220 RGB
1230 RGB
1240 RGB
1250 RGB
1260 RGB
1270 RGB
1280 RGB
1290 RGB
1300 RGB
1310 RGB
1320 RGB
1330 RGB
1340 RGB
R IGO»
SUBHOOT INI R I GOUT
COMMON AND DIMENSION FOK LISI PROCESSING ROUTINES
COMMON I HUG, ICALOR, I CHECK , I CLOCK , I CORE , I DUMM.2 , IDUMH4 , I FRST2
COMMON IFRST4.IFRST8, IC1VRHU, I T I ME 1, I T I Mfc2. I TYPE2 , JBUG, JCHECK
CCMMON MAXCRE.MAXlNT.MAXT.lTYPE 1
UIMFNSICN ICOKFI1000), COREI50)
FCUIVALFNCF(ICORE,CORE)
COMMON ANC DIMENSION FOR SIMULATION
COMMON /BD/ A9,ACRE,AHALOS,ANETYP,ANOHUN,ANORUT,ASNUPT,
1 AASSUN,A$SSUN,ASSUNK,AX1,AX2,AY1,AY2,B,CCL,CLKTM,,
2 COLFRE,COIHR,COLMLK,COITMZ,COM,PAP,CONA,CONB,
3 CONC,CONO,CONE,CONF,COSCOL,CORACR,COSLND,
4 CREHTS.CRUS/.CSHRTC.CSTHR.CTS.OAYS.DELDEP.OMTAVE.
5 [>MTMAX,OMTMIN,OmSlG,DOt.COL,DOLRIG,DOl_TON,
6 DOLTS,URO°AY,OROVRT,DSIC,DW,EVENT,FINDAY,
I H-ATNO,Fl.TLTMtFX,FY,HISC12,HISC13,H!SC14.
0010 RGO
0020 RGO
0030 KGO
0040 RGO
0050 RGO
0060 RGO
0070 RGO
0080 RGO
0090 RGO
0100 RGO
OHO RGO
0120 RGO
0130 RGO
0140 RGO
0150 RGO
0160 RGO
0170 RGO
0180 RGO
0190 KGO
0200 ROD
0210 KGO
0220 ISO
-------
II II TM t t ,\- I S( 1 ),HI ',( ,",,HlSr. i 2, HI St. )3iMISC t4,
'* M I ',( <* ^ f M Sf '. 1 1 H I SL <, '.
( PKWiiN /I'l / HtSlhl ,l< I Sllll ,11 I ',tU2,Hl SIU J.HI STU4,
T lClH(K,IN,IM(,KMl,inu,IRUNNO,IFI*L,JOW,JtRC.
7 MHI , lIKPt.L t J FRI'KI,,K ,K2iK4,K5f KAPIS>KINIRK ,
i KlNm ,Kr,IMF S.K IPUP.PAXLCtNAiNARtAtNtiNDA,
4 NCR . NN, NOR LI I .NO I I TStMlTRC , NO F RC2 .NO FRK ,
5 NCIHI ,NIWR t 1 ,NOVR F2.NOVR! J.NT ,ONCF .OPT*.
6 OHHH.OVI'AYL.OVKIK.PAYLBR.PFRUN.PNOMU.PNmtG.
I HRHH 1,1.0,1)1.02,03,114,05,06,07,08,1)9,0.10,
H 011,OMAX,CO,OU1AVF,OUIMAX,OOIM1N,OOISIG,
9 OlJIlMr,GUlFIM,OUF2,R,RGVKAX,RGVMIN,RlGKA
I C*M)N /Ml)/ HI(,HF1,K|G»«AX1RIGVFI,RKA,RKAA,RKH.KKH|1,RKCC.
1 RnM)Ic,,HMXUSR,RPXU'bT,RNO,RONNO,SCOl.ML.$MHRKF,
2 SKIf.Ml.StAF.SIMISF.SIRFML.SOMRUF, SOMFRK,
^ lARFA.THALOb.UWI.FIPFO.FNF TYPiINOHUNt
'• FONAGF, inltdS, !(jl ttlN,IOIWT,TRCtTRCSIN,TRFSi
•) IRHm,rHFMLtlKr[M/,|KIP,INK[)AY,tRKlU,TRLi
6 TRtnAi , iRpciii , IRPH in .iRi'tM, t SCOST.TSHR,
f ISIHCA,!S!M,IX,rY,UNACRF,UtHTY,V6LHAX,
H vriMN,VtLMimtV(IWUTiVFI. SOKi VELSr.Tt MATEi
'< HAU / ,HI , XDAY, YR S
DIM Nr, I (IN AHALDSI 21)) .ANETYPI 25 ) , ANOHUNI 25) f ANORUTI 25)
I ASNIJPT 125) ,AAS5UN(25I ,AX1(25) .AX2I25)
f AYM,'')) fAY2(2'i), HI IO),CCL(6) tCOLMLKCi)
1 I.URACKI4I ,C1S(6) ,EVENT(60) fHISC12(16l
« HIS(HI16),HISCHI16).HISC22(16),HISC?3(16)
•> HISC^'.I 16) ,HISC 321 1ft I.HISCUI 161 .H1SC3M 16)
(JlfFNSIf)N
1
?
)
HISFO1(161,HISFU2I16I,HISIU3(16),HIST04(16)
OPIMI60I .OVRFMI50) .PERONI4) ,00(50)
OUI!M(. I60),(JOI2I500I,ROAOISI25).STATI90)
TIHH60) .FONAGFI6) .TOTHTI50) .TRCI60) .TRIPI90I
IKKIUI50) .FRLI60) ,TSTMI 1000 I,WAIF 150) .
DAYSI2.3I. IFIHLI2.12). ODI I IMI 50,6 I, RKAAI4.2),
RKRBI4.2I, RKCCI4,2),TAREA(50,3),IHALDS(50,3),
2), TNETYP(50,3I, TNOHUNI50.3)
9 TRPRir, » THI'KIG • 1.
)IHL - THI INT )
JIHC « IUCINT)
IR1PI.IIHL I i TRIP! JTRL) « 1.
GAIL RANtPMIDNCF , TRFS.RDPTMI
IF I THLHAI .(.T.RMXUSK ) 00 TO R6- )4 )5<<718J6 I
X15 = f 15
10 K 1-K 1« 18 1467
K IsK 1-(K 1/f 351 «M35
RE IUKN
FSC
RNNR 000
RNNR 010
RNNR 020
RNNR 030
RNNK 040
RNNR 050
RNNR 060
RNNR 070
RNNR 080
RNNK 090
RNNK 100
RNNR 110
RNNR 120
RNNR 130
•IPFTC RUNDI*
RUNOAT
0010RONO
0020RUND
0030RUNO
-------
C UPXUN »M> DIPfNSIliN KlK (IS! PK(CISSINO RUUllWS
r OPMfIN II'UI,, 1C Al I;H, ICHI CK , 1C I OCK , H.URF , IL1UMM2. IOUHM4, 1FRST2
f ( PMIIN MRS i<, ,iiKr>Tii,i(ivKHi!,iTiPFi,iTi*F2,iTYPF2,jBUG .JCHICK
I I'PPTN PAXf Kl ,l"AXINI,MA»l,ITYPI 1
DIPINSHN luiRiitoori, (IIRMSOI
i cui VAI i M i ( ir.iiRt ,(.ORF i
CUPPON AND OIPINSION FOR SIMULATION
(I PMDN /hi)/ A9,ACHl,AHAtl)S,ANFTYP,ANOHUN,ANOHUT,ASNUPT,
I AASSUN,ASSSUN,ASSUNK,AXltAX2,AYl,AY2,B,CCl,CLKTN,
2 r.fll F RF ,( III I'M, f 1)1 PI K, COL TMZ ,COMPAP,CnNA,CUNB,
) (.(INI .CIINO.r UNI ,f(lNF .COSCOL ,CUR ACR,CUSLNO,
4 LRIMTS,(.HIIS/,(SIIHTC,C sniH.CTS.UAYS.uriDFp.DMTAvF,
S DM TM AX, CM If IN. DM IS 1C, ,001 CIJL , DULR I (, , IIUL T ON ,
6 Dili TS.ORDPAY.UKIIVKT ,C SLC ,t)H.E VFM ,F INDAY,
» FIAINn,FLTItM,IX,(Y,HISC12,HlSC13,HISCl«i,
II H ISC?/i III SC? ),Hr,C24,HI SC. )?,HI SC 1 I, HI SC34,
9 HI SL42.HI SL4 tiHI SCt*
(IIPPIIN /H[i/ HI S 11)1 ,H| STUI ,ll| STU2.Hl STU3.HI SIU4 ,
ICUI IK, IN. IMCKMT,IOU,IRUNNO,1TIML.JDH,JTRC,
I I R I , I I M I' f I .JIKI'KI, ,K,K?,K*lKSlKAI>TS.KINrKKi
KIN'RI,KSTMFS,MPUI',PAXIU,NA,NARFA,NC ,NOA.
<. N(]K,NN,MIRUI ,N(H I t S , NO I KC , Nil T «C '/ ,NO I «K ,
S NO I HI .NUVKT 1 iNHVKT2iNOVKr 1. NT , IJNCfc ,01'TM,
6 URHK.UVI'AYl ,UVI( IM.PAYLHK , Pf RUN , PNUMU , PNUS I G ,
I PRHII r, 00, Ul, 0?, CjJ,a. 06,07, «H,U'), 010.
n (Jl 1 .UMAX ,CO,UUI AVI .OUIMAX.UUIMIN, UU I blG.
1 UUI IM(, ,OUI I IH.UUtJ.H.RC-VMAX.RCVMIN.Klr.KA
COHMUN /Hn/ KICKIl.R IGMAX.R IGVFL , RKA , HKAA ,RKH .HKHB ,RKCC .
1 HOADIS.flMXDSR.RMXDSI.RNn.RUNNO.SCULML.SMHRKT,
2 MUr,ML,STAT,STHFST,STRFML,SUMRur,SUMrRK.
3 lAmA.THALOS.TIKF.TIHEO.INfTYPtlNUHUN,
MISf.^«(16).HISC12ll6l,MISC33(16),HISC3<,(16).
6 HISC',2(l'il,HISC'.JI16l,HISC'i'i(l6),HIST01(16),
' HISnj 1116),HlsrU2(16),HISTU3ll6),HlSH) ft ./( (II I Rl
li (Noinr.Nt .01
ii icui i m .m.2.
r,n KJ 21 ;
i (,o ru 2u
OOiOHUNU
OO'jORUNI)
00 /ORDND
OOBORUNU
0090RUNO
0100RUNO
01 If) RUN!)
0120KIINI)
01 ) OR UNO
OltORUNR
01 VJRUNI)
OI60PUNO
01 70RUNO
01HORUNU
0190RUMJ
0200RUNU
0210HUNO
0220RUND
0230RUND
02".OKUNU
0250RUNO
0260»UNU
1RIHAL,RUNNO,K,NOTKC,09,alO
TRLHALtRUNNU,K,NUFHC,U9.UIO
201
202 DAYSLT » 3.
20) (,( III 20'j
H", IIAYSLf = *.
^05 SfiS = 0.
206 i;r 20H I - l.NAHFA
20 I S(.S ' S6S » ANOHUNI I )
206 U;M INUC
A»FP[)I> ^ (PtHUNIl) «PERUN12I »PERUNI3) • PERUNCil) / A.
209 /NfvNN • S6S • PNOMU • OAYSLC • AVEPOP • COLFRE • 10.
NCIKC = ZNNNN / I 6. *R I(,MAX« I69.-TRLHAL ) I
211 IF INUTHC.LT.2) NOTRC * 2
212 IF (N(IIRC.GI.IO) r,0 TO 2U
213 Or TO 21?
21". KR lit I HU,215I
215 FUHMATI1H .67HMORF THAN 10 TRACTORS NEEOFD, AREA BEING SIMULATED
1UST 11 F SPALLFR.)
ST( p
21 f N( TRL2 = NOTRC * 50
IRLINNI) " RUNN'J
JSN " ASSSUN « 1.
(,l TU (10.11,11). JSN
10 Hlf.PAX > ') '< ')
-------
58
• I H r F ( ', I A (. •
MIIIWIHIFINF SMC 1N1,N,>,X,M) AN , > I (,,MAX f MIN )
HIM NMClN XIII
M t A L Ml AN,MAX,WIN
NCI=N7-N1
N I ,NM|t 1
XNiN I
MAX-XIN1 I
MN'XINI I
MI AN = n.
VAH'0.
II' 10 1 • NI.N2
F. MAX I Gl] II) 5
.r,f .MINI r,o TO 9
I
IF I XI I
MAX-XI
(,( IU
5 IF (XI |
MIN»X(
9 Ml AN = MtAN»X| I I
VAR'VARtXI I I «X( I )
10 UIMINUF
Ml AN = MF AN/XN
SH.'SOHF ( VAR/XN - MFAN'MFANI
Rl TURN
F Nil
0010 SIC
00?0 StC
oo>o src
0040 SIC
00">0 StC
0060 STC
0070 STC
0080 SIC
0090 STC
0100 STC
0110 STC
0130 STC
OHO STC
oi*o src
0150 SIC
0160 STC
0170 STC
0180 STC
0190 STC
0200 src
0210 STC
0220 STC
0230 STC
0240 STC
unrtc T«HI«
SUBROUTINE TAIH 1
c
C COMMON AND DIMENSION FOR USt PROCESSING ROUTINES
C
COMMON IBUC.ICALOK, I CHFCK , 1 CLOCK , I CORE , I OUM,M,2 , 1 DUM.M4 , I FRST2
COMMON lFRST4,IFRSTB,tOVRHO,mMEl,ITIMF2, I T VPfc 2 , JBUG, JCHECK
CnCKON MAXCRE,MAXINT,MAXT,I!YPE1
DIKfNSICN ICORFI IOOCI ,
f CUIVAL FNCH K,t)«F .CORE I
CflPMON AND DIMENSION FOR SIMULATION
/HO/ «>),ACRF,AHAlOS,ANFTYP,ANnHUN,ANORllT,ASNUPT,
I AASI>UN,ASSSUN,ASSUNK,AXl,AX?,AVliAV2,8,CCL.CLKTM,
2 CnLFRF,C(JLHR,C()LMLK,C()LTMZ,COMPAP,CriNA,CONHi
3 CONC,(.ONr>tC(INr,CONF-,COSCOL,CORACR,COSLND,
4 CRtWTS,r,RUSZ,CSHKTC,CSTHR,CTS.DAVStOELOEP,DMTAVEt
*> LmtMAX.UKTMIN.fJMTSIG.DOLCOL.OOLRlG.DOLTfmt
ft DO LrStnRFJPAYiURriVRTtOSLCtDW, EVENT, F INOAY,
1 FLArNF!,HLTLTM,rX,FY,HISC12,HISC13,HISClJTRPRG,K,K2,K'itK5,KAPTS>KINTRKf
i KINrRL.KSTMFS.KTHDP.PAXLaiNA.NAHEA.NC.NOA,
4 NnR,NN,NORl)r,NOFLTS.NOrRC.NOTINDS IG,
7 PR ItFLI, 00, 01,02, 03, 04, 1)5, 06, 07, 08, 09, 010,
R Q11,QMAX,OQ,UIIIAVC,QUIMAX,QUIMIN,OUIS1G,
1 UUI TMC.gUI rrn,(JUT2,R,f!
6 HISC?4(lft),HISCJ2(l6l,HISCU(16l,HlSC14ll6l,
6 HISC42I 1AI,HISC4)( 16I.HISC44I 16I.HISTD1I16I,
7 mSTUl(16l,HISfU?ll6l,HISTU3(16l,HISTU4(16l,
8 OPTHI60) ,OVRTM(50) ,PERUN(4I ,00(50) .
9 OU1TMCI60),OUT?I300),ROAOISI25I,STAT(90I
UIMFNSICN T1HEI60) ,T(JNAGE(6I ,TOTHT(50) .TRCI601 .TRIPI90I
1 TRKLOI50) .TRL160I , TSTM ( 1000 1 , WATF ( 50 1 ,
2 DAYSI2.3), ITINLI2,12), QUI TTM ( 50 , 6 I , RKAAI4.2I,
3 RKRBI4.2I, RKCC ( 4 , 2 I , T ARE A( 50. 3 I , THALOS ( 50, 3 I ,
4 TIMFQI 2, 12), TNETYP(50,3), TNOHUN(50,3I
CC 100 I * l.NAREA
IF 1010.EC.0.) GO TO 10
AHAL()S(l) = (ABS(AXl(l)-AX2ll))«ABSIAYlllt-AY2(I)]«ROADIS(l))
1 / 5280.
X =. AHALCSI I I
IF IX.GL. l.?5)Gll TO 21
0010
0020
0030
0040
0050
0060
0070
0080
0090
0100
0110
0120
01 30
0140
0150
0160
01 70
0180
0190
0200
0210
0220
0230
0240
0250
0260
0? 70
0280
0290
0300
0310
0320
0330
0340
0350
0360
0370
0380
0390
0400
0410
04?0
0430
0440
0450
0460
0470
0480
0490
0500
0510
0520
0530
, 0540
0550
0560
TB!
TB1
TBI
TB1
TBI
TBI
TBI
TB!
TBI
TBI
TBI
TBI
FBI
TBI
TBI
TBI
TBI
TBI
TBI
TBI
TBI
TBI
TBI
TBI
TBI
TBI
TBI
TBI
TBI
TBI
TBI
TBI
TBI
TBI
TBI
TBI
TBI
FBI
TBI
TBI
TBI
TBI
TBI
TBI
TBI
TBI
TBI
TBI
TBI
TBI
TBI
TBI
TBI
TBI
TBI
TBI
0570 TBI
0580 TBI
0590 TBI
0600 TBI
0610 TBI
0620 TBI
0630 TBI
0640 TBI
0650 TBI
Ofc',0 TBI
-------
59
l,( FIJ 21
10 AI'AI IJSI I I • FRLHAL
X -- A X A L I, S I I >
21
NC
ANF I Yl'l I )
cm i nt
AASSDM
AASSDM
AM1RU1 (
NF HI/I •
60 AM1HUM
ASMJPI I
Y lASNU
II I Y.I
WHIM ' MMRDF
f,(. Ill 60
100 ( F NI INUI
m TIIKN
FM)
KKAAINN.NCI * IRKBBINN.NCI>X) »IHKCCINN,NCI•X«X I
ASSIINK • AASSUM 11
ANDMUNI I I/AASSUM I I
ANURUT II) > 0.75
MCIKDI
Af.cli'INI I ) /ANIIRUI I I I
I I I I
. 1400. I GFI FD 1 00
1
0670 IBI
06HO FBI
06VO FBI
0700 FBI
0710 FBI
0720 FBI
07)0 FBI
0740 FBI
0750 TBI
0760 TBI
0770 tBl
0780 TBI
0790 TBI
OHOO IBI
0810 FBI
OH20 TBI
0830 TBI
0840 TBI
0850 TBI
0860 TBI
HBFTC TAB2«
SUBROUTINE TAB12
fnCNON AND IIIPI-NS ll'N FOR LISI PROCESSING ROUTINES
CfMNHN I BUG,ICAl OR,I CHECK,1 CLOCK,I CORE,10UMM2,IFHJMM4,IFRST2
(.F1CMUN irRST4,IFRSI8,lnVRHF),IFIHtl,ITIMt2,IFYPfc2,JBUG,JCHECK
CCJMfUN HAXfRF,MAXINT,MAXT,IFYPtl
DIPCNSICN IUIRE ( 1000) , CURE 150)
FCUIVALFNU (ICfJI'l .CORF)
CnPPON ANF) DIMENSION FOR SIMULATION
r.CKMDN /DO/ A9, Af.RF.AHALFJS, ANETYP, ANOHUN, ANORUT , ASNUPT ,
1 AASMJN,ASSSUN,ASSUNK,AX1,AX2,AY1,AY2,B,CCL,CLKTM,
2 CFH IRE,COIHR,CULCLK,COLTK7.COMP&P,CUNA,CUN8,
) COM. ,f, riND,C(JNF,CUNF,COSCnL,CORAC R.CUSINE),
4 r.RtWFS,f.KIJS/,CSH«TC,CSTHR,CTS,DAY$,DFLDEP.DMTAVE,
5 UMFMAX.UMTMIN,OPISIG,DE)LC()L,nOLRIGtOULTON,
6 (JOL !S,l)RDPAY,l)R(IVRF,OSLC,l)W,EVtNT,F INOAY,
I FLAINO,FLTLTM,rx,FY,HISC.12,MISCl),HISC14,
8 H !',(.? 2, HI SC2),M[SC24,HISC32,HISC)3,HISC34,
9 MlSC42.HISC4),HISC44
CtifMUN /BOX HISFni,HISTUl,HISTU2,HISTU3,HISTU4,
If OLI R, INt I NORM I , IOU.1RUNNU, ITIHL.JUH,JTRCt
[) IfTNS ICN
l)|fEN',l(IN
KINFRL,KSIMrS,KIMDP,CAXLQ,NA.NARE»,NC,NOA,
NI!R,NN,NnRUF,NOILTS,NOTRC,NnTRC2,NOTRK,
NUTRL.NOVRTl.NUVRT2,NOVRT3,NT,ONCE,OPTM,
aRHR,OVPAYL,FJVRTM,PAYLBR,PtRUN,PNDMU,PNDSIG,
PRBFLT.UO,01,02,U3,U4,Q5,Q6,07,08,09,010,
(J11,U«AX,QO,OUIAVF.,OUIMAX,OUIMIN,OUIS1G,
OUITMC.CUITIMtOUIZ.R.RGVMAX.RGVMlN.RIGKA
RIGKfl,Rlr,t«AX,RIGVEL,RKA,RKAA,RKB,RKBB,RKCC,
RDADIS.RNXUSR.RUXFISF.RNO.RUNNO.SCLILML.SMMRKT,
SrtlGMt,SIAT,STMF ST,STRFML, SUMRUT ,SVJMTRK,
TARE-A.THALF)S.rlMElTIHEO,TNtTYP,TNOHUNi
FONAGF,TOFCU!,,FIJTTFJN,TOTWT,TRC,TRCSIN,TRES,
FRFHR,TMFfl,FRFIMZ,TRIP,TRKL)AY,TRKLU,TRL,
IRLHAL, TMPC (Jl.TRPR 1C, TRPTM,TS"C CIST, TSHR,
TSLHPA,TSTM,FX,IY,UNACRC,UTILTY,VELMAX,
VCLMIN,VELMUR,VFLHUT,VELSGR,VELSGT,WATE,
MATE-/ ,XT , XFJAY, YRS
AMALUS(75),AM£FY1M25),ANOHUM25I,ANORUTI25»,
ASNUPI I 25 I.AASSUNI25I,AX1 I 25 I ,AX2(25I ,
*YU?M .AY7I751, B< 10 > ,Cf.L 1 6 ) .COIMLK I 4 ) ,
CIJRArR|4l .CFSI6I ,EV(NT(60) ,HISC12(16),
H1SCM(16),HISC14I16I,H15C22I16),H1SC23(16),
HISC?'. (161,III SO2I16I,HI SC 33(161,HI SC34I16),
HIS(.4?(16I.HIsr.4)(lM,HISC44(16I.HIST()l(16),
HISIIJ1 ( 16) ,HI SIU2I 16) ,HI STU3I 16) ,HI STU4I 16) ,
DPTHI/iO) ,(IVRTM(50) ,P(RUN(4) ,00(50) ,
UUIIMC(60>,OltF2MflO),RnADIS(25),STAT(90)
TIMII60) .I(INAfiFI6l .FOFHFI50) ,TRC(60I ,TRIP(90)
TRKL1K50I ,FRL(60) , F S T H ( 1000 I , H A T E ( 50 ) ,
l)AYi(7,1), 1I1MI(2,12), UUI T IMI50.6 ) , RKAA(4,2I,
RKBBI '< ,2 I . RKr.C(4,?),lARFA(50,3),THALOSI50,3),
Flneu(2,12), INE.TYPI 50,31 , TNQHUM50,3)
E)C 10 I = l.NAREA
SOfRUT =; SUMRUT » ANORUT(l)
10 CCNFINUE
1RKOAY - SUMRUT • CCLFRE
NCFRK = (TRKDAY/6. • 0.99)
XHAY = NCTRK
IF INOTRK.r.T. 501 GO TO 210
0010 TB2
0020 TB2
0030 TB2
0040 TB2
0050 TB2
0060 TB2
0070 TB2
OOHO TB2
0090 TB2
0100 TB2
0110 TB2
0120 TB2
0130 TB2
0140 TB2
0150 TB2
0160 TB2
0170 TB2
01BO T82
0190 TB2
0200 TB2
0210 TB2
0220 TB2
0230 TB2
0240 TB2
0250 IB2
0260 TB2
0270 TB2
0280 TB2
0290 TB2
0300 TH2
0310 TB2
0320 TB2
03)0 TB2
0340 TB2
0350 TB2
0360 TB2
0370 TB2
0380 TB2
0390 T B 2
0400 TB2
0410 TB2
0420 T82
0430 TB2
0440 TB2
0450 TB2
0460 TB2
0470 TB2
0480 TB2
0490 TB2
0500 TB2
0510 TB2
0520 TB2
05)0 TB2
0540 TB2
0550 TB2
0560 FB2
0570 TB2
0580 FB2
0590 TB2
0600 IB2
0610 TEI2
0620 TB2
06)0 TB2
0640 TB2
0650 TB2
0660 TB2
0670 TB2
0680 TB2
0690 TB2
-------
6o
?1(.
ii
I 1
200
100
600
37
4 1
39
173
l 74
IBS
274
275
1 75
21 1
1,1 111 11
hk 1 II 1111,1,')
fMKMAIIll- ,6SHMI|RF THAN 50 IHUCKb NEFOiO
II HF SMAI 1 1 K. )
SII'P
ZN « 0
1= 1
(;r 100 * I.NUTRK
1)1 2CO • I. NOR
I AHI Al 1 J) • 1
Tt'JHIlSI J 1 - AHALOSIL)
INF 1 YPI J 1 * ANE TYPI L )
IKC HUM J) « AiNUPT ( L 1
/N = /N 1.
XI) - AN HUUl 1
IF 1/N.N(.X13) f,U Hi 200
It* « 0.
L ' L • 1
If I L .1 1 -NAKEA 1 GO 10 200
Ijl III ft 00
CI,KT IMJt
CTM INUf
JCOIK • rtlLFHI - 1.
00 Tu (37.47), JUILK
733 * 'SiOELDEPiOMrAVEi
5 DMTM.AX.DMTMlN.UMTSIG.OOLCOLtDOLRIG.OOLTUN,
6 UOLTS,ORDPAY,DROVRT,OSLC,DW,EVENTiFINDAY,
7 FLArNO,FLTLTM,FX.FY,FIISC12iHISCl3iMlSC14,
8 HISC22,HlSC23iHlSC24,HISC32,HlSC33iHISC34,
9 HISC42.HISC43iHISC44
COMMON /BO/ HISTIM.HI STU 1, H 1 S TU2 ,H 1 S TU3, H I S TU4 .
1 ICOLFR,IN.1NCRMI,IOO.IRUNNO,ITIMLtJDW.JTRC,
2 JTRL,JTRPCLIKINTRK,
3 KlNIRL,KSTMFSiKIMDP,MAXLQ,NA,NAREA,NC,NI)A.
4 NCR,NN,NORUT,NOfLTS,NOTRCiNOTRC2iNOIKK,
5 NOTRL.NOVRTl,NOVRT2tNOVR!3iNTtONC£.UPTM,
6 URHR.OVPAYL,OVRIM,PAYLflRtPERUNtPNDMu,PNOSIGi
7 PRRFLI,UOI01>U2,03,64,05,06,07,08,^9,010,
0010 TBP
0020 TBP
0030 TBP
0040 TBP
0050 TBP
0060 TBP
0070 TBP
0080 TBP
0090 TUP
0100 TBP
0110 TBP
0120 TBP
0130 TBP
0140 TBP
0150 TBP
0160 TBP
0170 TBP
0180 fHP
0190 TBP
0200 TBP
0210 TBP
0220 TBP
0230 TBP
0240 TBP
0250 TBP
0260 TBP
0270 TBP
02HO TBP
0290 IBP
0300 TBP
OHO IBP
-------
61
c
c
c
c
c
c
c
c
c
0021
8022
802 3
H024
8025
8026
802 7
8127
8028
8128
8030
8029
80 H
21
31
1 S,MMr,IIMfCJ,INtFYPf!NUHUN, 0370
4 ONAT.f , TDK IIS, TUT ION, IIII Wt , THC, TRCSIN, IRF S, 0380
r> PF IIII , Tl'l Ml , IRF | MZ , TH II', IPKOAY, 1 RKl [), IRL , 0390
ft Ml HAl , IWPUIl , IKI'R Id, IKHIM, IST.ilSI , TSMR, 0400
7 SI BPA, TSTM, IX, 1 Y.USACRF ,UI U TY.VFLMAX, 0410
H vi i MM, vr t HUH, vi i MUT .vrLsr.R, VFLSf.r ,HA IF , 0420
1 HAII / ,HT , XDAY, Yl< ', 0430
III ff Nr, 1 I,N AHAIIlS(25),ANI T YP | 25 I .ANIJHUNI ? ', ) , A NOR U I 1 2 5 1 , 0440
1 ASNUPI I 25 1 .AASSUN 1 25 1 ,AX1 I 25 1 .AX2I25I , 0450
2 AY1I25I .AY2I25I, B I 1 0 1 , CL L I 6 1 , ( OL Ml K I 4 1 , 0460
) f. RAIRI4I ,r.I'>!6l .FVfNTIAO) , H 1 SC 1 2 1 1 6 1 , 0470
4 HISt 1 31 16 ) .HISC 14 I 16 1 ,H 1 SC 221 1 fi } ,HI S(. 231 16 1 , 0480
5 Ml SC24I 161 .HISC 321 16 1 ,HI SC 331 161 ,HISC 341 16) , 0490
h HIS(.42U6> .HISC.4 M161 ,HlSC44( 1 (, ) ,HISU)1I 1 1> > , 0500
7 HI STU1 1 16) ,HI SIU2 ( 16 1 .HI STU 31 1 6 I ,Hl STU4 I 16 > , 0510
8 IIPIMIM)) .OVRTMI50I .PFRUNI4I ,UU(50) , 0520
9 OUMMCI60) ,(JUT2t 3001 ,RUADI 5125) ,STAT (901 0530
IMMINSKJN MM LI 60) , T I . N A G F ( 6 1 ,TOTwT(50) ,I4C(60) .TRIPI90) , 0540
1 FRKIDI50) .IKII60I , 1 S TM 1 1 000 I , WA T F 1 50 ) , 0550
2 ()AYM2,3>. IFIM1I2.12), UU 1 T TM ( 50 , 6 ) , RKAAI4.2), 0560
1 RKBBI4.2), RKCC 14,2) .TARFAI50, 31 , THALDS ( 50 , 3 ) , 0570
4 I IMF Q( 2, 12 ) , INI TYPI 5C, 3) , TNIIHUN 1 50 , 3 I 0580
0590
0600
DATA (.UN, 1 1N/6HICIINT I ,6HNUt U 1 / 0610
0620
1 ORMA1 1 !!• I/ IF -/ IH-/ IH-/ 111 -,4 3X.44HSOL ID WASTE COLLECTION S I MULAT IO06 30
IN RUN NUMB! R, 1 5/ 1H0.61X, 1 3HMOOFL THHE E / IH- / 1 H- ) 0640
KIKMAT 1 1HO,45X,50HTHI S IS A SIMULATION RUN ON A PORTION OF THF CI0650
1 TY/4 1 X.55HOF BALT1MORF, APPROXIMATELY DESCRIBED AS 'THAT TRACT/0660
2'.1 X,55HH('UNDFn UN THE NORTH BY THE CITY 1IMITS, ON THE EAST BY/ 0670
341X, 06BO
3 55HYI1RK AVI-NOF, ON THF SOUIH BY NORTH AVENUE, AND ON THE/4 IX , 250690
3HWFSI BY THE THY LIMITS. •) 0700
FORMAT! 1F'0,45X, 19HWITHIN THIS TRACT, 14, 27H RESIDENTIAL AREAS, EAC0710
IH CF 0720
1 /41X.55HPAHI ICULAR HOUSING DENSITY, HAVE BEEN GIVEN NUMBER DF0730
2S-/41X.20H1GNAT IUNS FROM 1 10 I3.32H. TABLE ONF BFLOW LISTS THE0740
3SI 0750
3 /4 IX, 3 3HARf AS AND DATA PERMNENT TO FACH.,I3,19H COLLECTION TRUCK0760
45, 0770
4/41X.26HAIL COMPACTfiR TYPE ARE OF I3.26H CUBIC YARD CAPACITY, HAVE0780
5/4 1X.22HBFEN ASSIGNED TO THESE, 13, 27H AREAS TO MAKE COLLECTION , 0790
6I3/41X, 15HTIMIS PER WEEK.) 0800
1 URMATI 1H0.45X.50HTHE CREWS ASSIGNED TO THE TRUCKS ARE A DRIVER A0810
1NP/41X.26HTWO LABORERS AT ALL TIMES.) 0820
FORMAT! 1H0.45X.50HTHE CREWS ASSIGNED TO THE TRUCKS ARE A DRIVER A0830
INIJ/4 1X.55HTHRFF LABORERS ON MONDAYS. TUESDAYS AND WEDNESDAYS, AND/0840
141X.55HA LRIVtR AND TWO LABORERS ON THE REMAINING DAYS. 1 0850
FfJRMAT 1 U'0,45X, 50HTABLE TWO LISTS THF ASSIGNED COLLECTION TRUCKS 0860
1 HY 0870
1 /4 1X.41HNUMBER AND lISJS DATA PERTINENT FOR EACH.I 0880
FORMAT! 1H1/1H-/ IH-/ IH /IH .59X.18H'" TABLE ONE •••/64X.2A6I 0890
) ORMAT 1 1H-, 0900
1 /,OX,S6HAREA NEIGHBOR- HOUSING TRUCKS ASSIGNED NUMBER 0910
2M IX, 56HNUMBER HOOD TYPC UNITS HAUL UNITS PER OF 0920
1/4 IX, 19X, 37HTOIAL MILFS TRUCK ROUTES /IH 0930
FORMAT < 1H1/1H-/1H-/1FI /IH ,59X,18H»»» TABLE TWO •••/64X.2A6) 0940
FORMAT 1 1H-, 0950
1 40X.56F-IRUCK ASSIGNED UNITS TO HAUL NEIGHBOR- DAYS TO 0960
2/4 IX, 56HNUMBFH TO AREA COLLECT DISTANCE HOOD TYPE COLLECT 0970
3/1H 1 0980
FORMAT III' .40X.2X.1 3,5X, 14, (,X, I5.2X.F7.2, 7X, 1 3.6X.A6) 0990
1000
FORMAT 8029 IS 1 OR IABLE 1 1010
FORMAT H030 IS FOR TABLE 2 1020
1030
FORMAII1I' ,40X, 2X , 1 3. 5X, I 3,6X, I 5 , 4 X , F 6 . 2 , 4 X , 17, 5X.I3) 1040
1 OI1MAI ( 1H1 ] 1050
1060
1 INF =0 10 70
WR I H ( IIJU.H021 1 IRUNNI] 1080
WR 1 II I 1 (Ml, 8022 1 1090
WRIIF(1(II,8023)NAHFA,NARFA,N()IRK,K1NTRK,NARFA,ICOIFR 1100
IF (Ll)t 1 Ml .F U.2. ) Gf) TO 21 1110
WR IU 1 II U, 8024 1 1120
U' TO 31 1 1 SO
WR 1 1 t I II U.H025) 1140
HR I Tt 1 ILU.8026 ) 1150
I INF * B 1 160
HR ITf ( IOU.8027 1 U 70
HR I II 1 ILU.B127 ) 1180
1190
i:C 8H 1 = 1 ,N«REA 1200
KLFTYI>=AN( TYPI 11 1210
KLri'IIN=AM HUN! 1 1 1220
KLNUI'T -ASNUPI (II 12 30
IBP
nip
TBP
TUP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
-------
62
Kl (JRIM . AM1RIIT I I I
WH I IH 1UII,>U)29) I ,Kl F TYP.KI OHUN, AHALOSI I I >KLNOPT ,KLOR1JT
I INI M INI > I
IF( I INI -I I.'.HI (,0 TO Bfl
I INE=H
HR ITEI IOU.H028) CflN.TIN
WHI It! 1011,8128)
88 f.riMINUF
LINF..8
MR t TFI 1011,0028)
WRITFI100,8128)
K5 - CWfltF - 1.
00 91 I
DO 99 J
JNETYP •
JARFA =
• l.NCTRK
> 1, NOR
TNF.TYPII , J)
TAREAII,JI
KLOHONiTNOHUNI I,J)
WR|Tl( 100,8030) I,J»REA,KLOHON,!HALOS(I,J),JNETYP.DAYS(K5,J)
I INE'LINFM
IF(LINb.LT.4B) GO TO 99
LINt*8
MRITFIIOU.8028) CON,TIN
WHITE!100,81281
99 CONTINUE
91 CONTINUE
URITFI100,8031)
RETURN
FND
1?60
1?70
1?HO
1?90
UOO
1310
1320
1330
13*0
1350
1360
1370
1380
1390
1*00
1410
1420
1430
1440
1450
1460
1470
1480
1490
1500
1510
1520
1530
1540
TBP
TBP
TBP
TBP
TBP
TBP
IBP
TBP
fBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
TBP
»I6FTC TIME*
SUBROUTINE TlHt*
CIJHMON AND DIMENSION FOR LIST PROCESSING ROUTINES
COMMON IP,UG,ICALDR,ICHECK,ICLOCK,ICORE,IDUMM2,IDU*M4,IFRSTZ
COMMON IFRSI4iIFRSTB,IOVRHD.ITI ME 1,ITI ME 2,ITYPE2>JBUG>JCHECK
COMMON MAXCRE»MAXINTtMAXT,ITYPEl
DIMENSION ICOREI1000). CORFI50)
I HI II VALENCE ( ICORF, CORE*
COMMON AND DIMENSION FOR SIMULATION
COMMON /HO/ A9>ACHEiAHALDSiANFTYP>ANOHUN,ANQAUT,ASNUPT>
1 AASSIJN,ASSSUN,ASSUNKfAXl,AX2.AYl,AY?,B,CCL,ClKTM,
? COLFRF.COLHR,COLMLK,COLTM/.,COMPAP,CONA,CONB,
1 CONC.CaNO.CtlNE.CONF.COSCOLtCORACRtCOSLNO,
4 CREWTS,CRUS/,CSHRTC,CSTHR,CTS,DAYS,OELOEP,DMTAVEt
5 DMTMAx.DMTMIN.DMTSIGtOOLCOLfOOLRIG.OOLTON,
6 OOLTS,OROPAYtOROVRT,OSLC,OM,EVENT,FINDAY,
7 FLATNO,FLTLTM,FX,FY,HISC12»HISC13fHISC14,
8 HISC22,HISC23iHISC24.HISC32,HISC33.HISC34,
9 HISC42tHlSC43.HISC44
COMMON /BD/ HISTD1,HISTU1,HISTU2,HISTU3,HISTU4,
1 ICnLFR.IN.INCRMT.lOU.lRUNNO.ITtMl.JOM.JTRC,
2 JTRL.JTRPCL,JTRPRGlK,K2,K4.K5.KAPTStKINTRKt
3 KINFRLrKSTMFS.KTMDP.MAXLQ.NA.NAREA.NC.NDA,
1 NDR.NN,NORUT,NOFLTS,NOTRC,NOTRC2,NOTRK,
5 NOTRL,NOVRTlfNOVRT2,NaVRT3iNT,ONCE.OPTMf
6 ORHR,OVPAYL,OVRTM,PAYLBR,PERUNtPNDMU.PNDSI6,
7 PRBFLT,00,UlfC2.Q3i04,05,Q6,Q7.08.U9tQ10l
8 Qll,UMAX,QO,OUIAVEtQUIMAX,OUIMIN,QUISIO,
9 aUlTMC,OUlTTM.OUT2,R,RGVMAX.RGVMIN,RIGKA
COMMON /RD/ RIGKB,RIGMAX.KIGVEL.KKA.RKAA.RHB.RKBB.RKCC,
1 ROADIS.RMXDSRt)>MXOST>RND,RUNNO.SCOLML,SMMRKT,
2 SRIGML,STAT,STMFST,STRFHL,SUMRUT,SUMTRK,
3 I»RFA,THALDS,IIHE.TIMEO.TNETYP.TNOHUN,
4 IONAGE,IOTCOS.TU1TONirOTHT.TRC.TRCSIN.TRES,
5 TRFHRrTRFML,TRFIM2tTRIP,TRKDAY,TRKLD,TRLt
6 TRLHAL,TRPC()L,TRPRIC,TRPTM,TSCOST,TSHR,
7 TSLBPA,1STM,IX,TY,UNACRE,UTILTY,VELMAX,
8 VELMIN.VELMURiVLLHUTiVELSGRtVELSGTtMATEt
9 WATEZ.WT.XOAY.YRS
DIMENSION AHALOS<25I,ANETYPI25),ANOHUN(25I,ANORUTI2S),
1 4SNUPH25).AASSUNI25),AX1I 25) ,AX2(25) ,
2 AY1I25) .AY2I25I, BI 101tCCL16).COLMLKI41 .
3 CORACRI4) .CTSI6) ,EVENr(60) ,HISCI2(16),
4 HISC13I16),HISC14I16I.HISC22I161.HISC23I16) ,
5 HISC24(16).HISC3?ll6)iHISC33ll6).HlSC34(16)t
6 HISC42I16),H1SC43I16I,HISC44I16),HISTD1I16),
7 HISTU1(16).HISTU2I16)|HISTU3I16),HISTU4I16),
8 OPTMI60) .OVRTMI50) .PERUNI4) .00150) ,
9 OUITMC(60>.OUT2I300),ROADIS(25),STAT(90)
DIMENSION TIMEI60) ,TONAGE(6I |TOTWT(50) ,r«C(60) t7RIP(90J
1 TRKLDI50) .TRLI6CI •TSTMI10001.WATE150) i
2 OAYSI2.3), ITIMLI2.12), QUITTM(50,6), RKAAI4.2),
1 RKHBI4.2), RKCCI4,2),TAREA(50,3I,THALOS(50,3),
0010 TIM
0020 TIM
0030 TIM
0040 TIM
0050 TIM
OOfcO TIM
0070 TIM
0080 TIM
0090 TIM
0100 TIM
0110 TIM
0120 TIM
0130 TIM
0140 TIM
0150 TIM
0160 TIM
0170 TIM
0180 TIM
0190 TIM
0200 TIM
0210 TIM
0220 TIM
0230 TIM
0240 TIM
0250 TIM
0260 TIM
0270 TIM
0280 TIM
0290 TIM
0300 TIM
0310 TIM
0320 TIM
0330 TIM
0340 TIM
0350 TIM
0360 TIM
0370 TIM
0380 TIM
0390 TIM
0400 TIM
0410 TIM
0420 TIM
0430 TIM
0440 TIM
0450 TIM
0460 TIM
0470 TIM
0480 TIM
0490 TIM
0500 TIM
0510 TIM
0520 TIM
0530 TIM
0540 TIM
0550 TIM
0560 TIM
0570 TIM
0580 TIM
-------
63
IIMtm2,l<>), INI I YPI50, 3) , IMJHUf4l 'JO, »)
SI I II1NU.4, U.ALDH I
lllJKt I IUNO« 1 I/ 1U
ILOKl- I IONOM I
| 1UN(1 « ) )
JU <>(.
1001 CAU
IT IMH
IIYI'll
M • ICOHI
1021 ICIOLK • uiMFi
JCI OCK . IC.I OCK
f,( 1U ( 10,20, 30.40.40
1004 Ml IUHN
10 CM L THAI 1C
or, to 100
20 CAU CtllfCT
Of! ID 100
10 (,AI I IRAf If.
GO TU ICO
40 CALL HI Sf SI I IDNO)
IF (f INOAYiF 0.99. I GO 10 POO
G(. 10 ICO
60 U)M I Nut
55 C«l I RIU UT
(it) in ion
65 LALL RIGPAK
IF I f INUAYif-u.99. I GO Id 200
100 ITYPf-2 • FVINTIM) « .5
It [Kb? ' T IMf INI) . .5
ICORH IDNIH 3) » NT
(,20 T1H
0630 IIM
0640 IIM
0650 IIM
0660 TIM
06(0 TIM
06BO IIM
0690 TIM
0700 TIM
0710 TIM
0720 TIM
07}0 TIM
or«.o TIM
0750 TIM
0760 IIM
0770 TIM
0780 TIM
0790 TIM
0800
OS10
0620 TIM
0830 TIM
0840 TIM
0850 TIM
0060 TIM
08/0 TIM
0880 TIM
0890 tlM
TIM
TIM
• IflFIC IRAf •
SUHROUTINt TRAF1C
C
COKCUN AND DIMENSION FOR LIST PROCESSING ROUTINES
COPMON I BUG, ICA1 I)H, ICHf CK, Id QCK, ICORC, IUUMM2, I DUMM4 , IFRSI2
CtlfWON URSI4ilIRSIfl,lOVHHD,lIIMritlTlMF2fITYPE2.JBl)CfJCHECK
CfifMON CAXCRItMAXINT,MAX 1,1 TYPE 1
DIMENSION ICflRt I 1000), f.rmtliOl
ECUIVALI:NCF(ICORF,r.OH( I
COMMON AND DIMENSION FOR SIMULATION
COMMON /Hf>/ A9, ACRE , AHA1 US, ANE T YP , ANOHUN, ANORUT , ASNUPT,
I AAS'jUN,AS3SUN,ASSUNK,AXl,AX2,AYl,AY2,B,CCLtCLKTM,
2 COLIRF.COIHR.COI ML K ,COL TMZ ,COMP AM ,CUNA ,CONB ,
i CONf. ,COND,CriNF,C(INF,COSCOL,CORACR,CUSLNO,
4 CREWIS.CRUSZ.CSHHTC.CSTHR, CIS. DAYS, UELOEP.OMTAve.
DMIMAX.IJMTMIN.DMISIG.OOLCOL.DULRIG.OOLTON,
OOLIS,DRUPAY,OR()VKT,OSLC,nw,EVENT,FINDAY,
FLATNO,FLTLTM,FX,FY,HISC12,HISC13,HISC14,
HISC?2,HI3C23,HISC24,HISC32,HISC33,HISC34,
HI SC42.HI SC43.MI SC44
CflKMUN /HD/ HISID1 ,HI S TIJ 1 , H I S TU2 . H I STU3.HISTU4,
ICOIFR,IN,INCRMT,IOU,IRUNNO,ITIML,JDW,JTRC,
? JTRI,JIRPCL,JTRPRG ,K,K2,K4,K5,KAPTS,KINTRK,
3 KINIRL.KSTMFS.KIMOP.MAXLO.NA.NAREA.NC.NDA,
4 NDR,NN,NURUI,NOI I T S.NOTRC .NOTRC2 , NOTRK,
5 NO I HI ,NOVRTl,NOVRT2,NOVRI3.Nr,ONCE,OPTM,
6 URHK,OVPAYL,OVRTM,PAYLBR,PERUN,PNDMU,PNDS1G,
7 PRUFL I, 00, 01 ,02,03, 04, 05, 06,07,08,09, 010,
8 Oll,QMAX,ug,QUIAVE,GUIMAX,UUIMlN,OUlSIG,
9 OUIIMC,OUItIM,QU!2,R,HGVMAX,RGVMIN,RIGKA
(.tlMMON /HI)/ RlGKd.R lr,MAX,RIGVF.L,RKA,RKAA,RKfl,RKB8,RKCC,
I ROAIJIS,RMXI)SH,RMXOST , RNO.RUNNO, SCOLML .iMWRKT,
2 SRIGML.bTAT.STm S I , S TRFML , SUMRUT , SUMTRK ,
) IAH(A,IH*LOS,TIMe,IIMEO,TNEIYP, TNOHUN,
4 IflNAf, f,l() TCDS, III ITON.TOTWT.TRC.TRCSIN, IRES.
5 |H(MK,IHrML,TRFIMZ,IRIP,TRKDAY,TRKI.D,TRl,
6 IRl HAl , I R PC 01. , IRPRIG.TRPTM.TSCOST, TSHR,
7 TSlKPA,!S!M,TX,IY,UNACRE,UTILTY,VELMAX,
8 VElMlN,VfLMUR,V(LMUT,VCLSGR,VELSGI,WATE,
9 WAIf /,WI , XOAY.YRS
I1IKI NS ICN AHALI)SI2')),ANrTYP(25),ANOHUNI25l ,ANOHUT(25) ,
I ASNUCTI 251 ,AAS9UN(?5>,AXU25) .AX2I25) ,
2 AYK25) ,AY2I25), B ( 1 0 I ,CCL I 6 ) ,COLMLK( 4 ) ,
3 CORACRI4I ,CIS(6I ,EVENT(60I .HISC12I16I,
4 HISC13(16),HISC14(16).HISC22(16),HISC23U6).
5 HISC24I16I,HISC 32I16),HISC33(16),HISC34I16I,
6 HISC42(ltltHISC43(16l,HlSC44(16l,HISI01(16l,
7 HISIUM16),HISIU?(16l,HISTU3(16l, HIST U4 (161,
8 OPTMI60I ,OVRTM(50) ,PERUN(4) ,00(501 ,
9 OU1IMC(60),UUT2(300),ROADIS(25),STAT(90I
DIMENSION I1MM60I ,TUNAGE(6) .TOTWTI50I ,TRC(60I .TRIPCJO)
1 IBKiniSO) ,THL(60) ,TSTM( 10001 .WATEI50I ,
? DAYSI2.3), ITIMLI2.1?). OU I T TMI 50 . 6 I , RKAAI4.2),
1 RKRRI4,2l, RKCCI4.2I ,TARfA(5O, 31 .THALOSI 50, 3) ,
'. MMIU(7,|2I, INf TYPISO, 1) . TNHHUNI 50,
-------
L
(.
*00 I'M » NUH
IF 1 THAI I'StNl ,NI)R ) .Gf.PMXOM 1 GO To 304
VH MU ' HKA t HKIUTt'AI DSINI , MM )
Gf ri) 306
304 Vt t MU • VII MU r
106 (All RAM.I'MI V[ IMRKnH,RKCC,
1 ROAOI S,RHX()SK,RMXDST,RND,RUNNO,SC01.Ml,SMWRKT,
2 SRIGML.STAT ,STMF ST , STRFML . SUHRUT , SUMTRK ,
3 lARrA.THAlDS.TIMF.TIMEQ.TNETYP, TNOHUN,
4 TONAGE.TUTCDS.TOTTON.TOTWT.TRC.TRCSIN.TRES.
5 TRFHR,IRFML,TRETM/,IRIP,TRKDAY,TRKLD,TRl,
A TRLHA.L, TRPC()L,TRPRIG,TRPTM,TSCaST,TSHR,
7 TSlliPA,TSTM,TX,IY,UNACRE,UTILTY,VELMAX,
8 VELMIN.VELMUR.VILMUT.VELSGR.VELSGT.WATE.
t MAIF/ ,MT, XDAY, YRS
DIMENSION AHALUSI 25) , ANE T YP 1 25 ) , ANOHUN ( 25 ) .ANORUT (25)
I ASNUPT I 251 ,AASSUN(25).AX1(25) .AX2I25)
? AYK25I .AY2I25I, 6 ( 10 ) ,CCL ( 6 ) .COLHLK ( 4 )
3 CORACRI4) .CTSI6I .EVENTI60) .HISC12I16)
4 H1SC13I 16) , HI SCI 4! 16) .HISC22I 161.H1SC23I 161
5 HISC/4I16I.HIS.: 32(16),H1SC33(16I,H1SC34(16)
A HISC42(16),HISC43I16),HISC44I16).HISII)1(16)
7 HISIUU16),HISTU2(16I,H1STU3(16),HISTU4I16I
8 OPTMI60) ,OVRTM(50t .PERUNI4) ,00(50)
9 OUITMCI60),OUT2(300),ROAOIS(25),STAT(')OI
DIMENSION IIMM60) .TONAGEI6) .TOTKTI50) ,TRC(60) .TR1P190I
1 TKKHK50) .TRLI60I , TSTM ( 1000 ) , MATE 1 50 1 ,
2 OAYSI2,3), IT1MLI2.12). QU1TTM(50.6), RKAA(4,2),
3 RKIHM4.2), RKCC(4,2I,TAREA(50,3) , THALDS I 50 , 3 ) .
* T(Mlqi2,12), INETYP(50,3I . TNaHUN150,3)
0600 TRF
0610 TRF
0620 TRF
06)0 TRF
0640 THF
Ofc50 TRF
0660 tRF
0670 TRF
0680 TRF
0690 TRF
0700 TRF
0710 TRF
0720 THF
0730 TRF
0740 TRF
0750 TRF
0760 TRF
0770 TRF
0780 TRF
07VO TRF
0800 TRF
0810 TRF
0820 TRF
0830 TRF
0840 TRF
0850 TRF
0860 TRF
0870 TRF
0880 TRF
0890 TRF
0900 TRF
0010 UNP
0020 UNP
0030 UNP
0040 UNP
0050 UNP
0060 UNP
0070 UNP
OOBO UNP
0090 UNP
0100 UNP
01 10 UNP
0120 UNP
01 40 UNP
0140 UNP
0150 UNP
0160 UNP
01 70 UNP
0180 UNP
0190 UNP
0200 UNP
0210 UNP
0220 UNP
0230 UNP
0240 UNP
0250 UNP
0260 UNP
0270 UNP
0280 UNP
0290 UNP
0300 UNP
0310 UNP
0320 UNP
0330 UNP
0340 UNP
0350 UNP
0360 UNP
0370 UNP
0180 UNP
0390 UNP
0400 UNP
0410 UNP
0420 UNP
0430 UNP
0440 UNP
0450 UNP
0460 UNP
0470 UNP
0480 UNP
0490 UNP
0500 UNP
05 IO UNP
0520 UNP
0530 UNP
, 0540 UNP
0550 UNP
0560 UNP
0570 UNP
0580 UNP
-------
K.HI ( K 1 '. ,2, i
If«! I ///I X, I2HA I
II RHIIH dINIJI I IfIN
IClfK.K
NiJMIll HI
« .I8.13HANFI
I HI HH HA'> ir
,IH/1X,
Ill (lllll.ll II I f](.K r J(.H[ (,K i If HFCK
( A I I'ANIC
4 1C I I. K . 0
2 II- luriHD/MAXINf
I 2a I HIIHI - I t -PAX INI
Rl TURN
F Nl,
0590 UNP
0600 UNP
0610 UNP
0620 UNP
06)0 UNP
0640 UNP
0650 UNP
0660 UNP
06 70 UNP
06HO UNP
0690 UNP
SIIIIRnill INF Ml FKSM
mcMIIN AND DIMINSIUN FOR LIS! PROCESSING
( f] KM I IN imir, , K ALDR, ICHFCK, K.IUCK, [CORE, I FJUMM2 , I DUMM4 t IFRST2
LMPM1IN UP SI'. , IFRSTH, IUVRHD, I I IMF 1, I T IMF?, I IYPF2, JBUG.JCHECK
fliKWCN KAXC Ml ,MAXIN!,HAXr,lIYPfl
i) lt>( NSK.N icuHiiinnoir r.iiRnso)
I till VAI I N< I I If IMF ,UMF I
r.HPMIJN AND IIIPfNSlnN FOR
CClf MUN /111)/ A'), AT Kf , A HAL I) Si ANF IVP.ANOHUN, ANURUT , ASNUPTt
1 AAr, SIIN.ASSMJN.A', SUNK,AXliAX?,AYl,AY2,B,CCL,CLKTM,
t toi i KT .(.oum.r.oi MK.roi \vi ,r.uMPAp,toNA,tnNB,
) I.ONC ,(,(IND ,(,HNe ,flJNF , CO SCni , CUKACR.Cn SL NO •
4 (R(HIr,,(RUSZ,tSHRIC,CSTHR,CrS,OAY5IDELOFP,DMTAVE,
•i IJMTMAX.IIMTMINf DM ISIGiODLtnL iDOLR 10, DDL TON,
6 UIJl Ib.URUPAY.DRUVRT.DSLC.DW.fcVENT.F INDAY,
7 FlATN(),FLTLTM,FX,FY,H|SCU,MISC13,HISCl't.
fl HIS(??,HlSC23,HlSCZ^fHISC32,HISC 33.HISC3'.,
"J Hl'>f.A?,HI SC ,CCl I 6 > .COLMLK < 4 )
CORACRI4) .CTSI6I .FVENTI60) ,HISC12(16I
HISC13(1A),MISC 14(16).MISC22I16),HISC23(16)
HISC24(16l,HISf. 32I16),HISC33(16),HISC34(16I
HISIU1I16I,HISTU2I16),HISTU3(16),HISFU4(16)
UPIMI60I ,(WRFM(50) ,P[RUN(4I ,00150)
UUIIMC(60),CJUT21300),ROAniS(25>,STAT(90)
F1MFI60) •T(IKA(,r-|6) .FOFHFI50) .TRCI60) .TRIPI'JO)
IRKIOISO) .IRtthOI ,TSTM(1000),HAFE150) ,
UAYSI2.ll, IFIMU2,12), OUI T IM I 50, 6 I , RK»AI4,2>,
KKHIH4.2). HKCf. I4,2),TARIA(50,3I,THALUSI50,3),
TlMr.012,1? It INf IYP(50,3) . INDHUN I 50 . 3 I
SRIGfL • TRPHIG • IRLHAL • 2.0
on 10 i«•
cnscoL -
r.-vcosr -
Tnil UN •
CCM INUE
TSCOSt
TOMON
CCL( I I
CISII I
TCNAGtI I
IOTCIJS » CCSCOL » TSCOSt
Dl'LCGL • CUSCOL/TCUTON
CCLRIG = TSCOSI/TOTTON
DOLTCN = TOTCOS/TOTTQN
CALL SI«Cll,K2,TSTf,DMTAVF,UMTSIG,DMTMAX,OMTMIN)
CALL STAC<1,K<,,OUT2,OUIAVF,UUIS1G,OUIMAX,QU1MIN)
SUfACt = CULHR 4 TRFHR » TSHR * ORHR
CCLHR = (CULHR / SUMACD " 100.
TRFHR i (TRfHR / SUfACT) • ICO.
t SI'H « ( ISHR / SUMACT I . 100.
0010 WKS
0020 HKS
0030 WKS
OO-iO HKS
0060 HKS
0060 HKS
0070 WKS
OOHO HKS
0090 HKS
0100 HKS
0110 HKS
0120 HKS
0130 HKS
0140 HKS
0150 HKS
0160 HKS
0170 WKS
01BO HKS
ODD HKS
0200 HKS
0210 HKS
0220 HKS
0230 HKS
0240 HKS
0250 HKS
0260 HKS
0270 HKS
02HO HKS
0290 HKS
0)00 HKS
0310 HKS
0320 HKS
0 1 iO HKS
0340 HKS
0350 HKS
0160 HKS
0370 HKS
03HO HKS
0390 HKS
0400 HKS
0410 HKS
0420 HKS
0430 HKS
0440 HKS
0450 HKS
0460 WKS
0470 HKS
0480 HKS
0490 HKS
0500 HKS
0510 HKS
0520 HKS
0530 HKS
0540 HKS
0550 HKS
0560 HKS
0570 HKS
0580 HKS
0590 HKS
0600 HKS
0()10 HKS
0620 HKS
0630 HKS
0640 HKS
0650 HKS
0660 HKS
0670 HKS
06HO HKS
0690 HKS
OTOO HKS
0710 HKS
0720 HKS
0730 HKS
0740 HKS
0750 HKS
0760 HKS
0770 HKS
0/HO HKS
-------
66
(iHI'U • (IHHK / SUMACI) • I'llJ.
ur; 100 J • ltl?
Ul -Ql • TIMFUI l , j)
loo rr r< I INIJI
on 200 J > 1,12
0? . 02 • TIMK<2,JI
ZOO CONTINUE
Of) 100 J » 1,12
riMfuu.J) • MMF-UII.J) • 100. / (01 » o.si
JOO U.MINUE
(in 400 J • 1,12
MMEm2,J) - TIMtQ12,J> • 100. / (02 » 0.5)
400 r.(
no 121 i « 71,90
IF I TRIP! I I.FQ.O. I CO TO 122
121 CnHMNUF
122 NI'TRL -1-71
Hf TURN
I NH
0/40 WKS
OHOO WKS
OHIO WKS
0820 WKS
0830 WKS
0840 WKS
0850 WKS
0860 WKS
0870 MKS
OB80 WKS
0890 WKS
0900 WKS
0910 WKS
0920 WKS
0930 WKS
0940 WKS
0950 WKS
0960 WKS
0970 WKS
09HO WKS
0990 WKS
1000 WKS
1010 WKS
10?0 WKS
1010 WKS
«IBFTC KI
0010 XIN
SUBROUTINE XINIT
AND DIMENSION FOR LIST PROCESSING ROUTINES
COMMON I BUG, ICALOR, I CHECK, If. LOCK, I CORE, IDUMM2, IDUM.M4, IFRST2
rnf MUN IFRSfi, IFHSTB, IOVHHU, I T I ME 1 , I TIME 2, I I YPE2 , JBUG, JCHECK
COCOON M»XCKE,MAXlNT,MAXt,ITYPEl
nicENsitiN ir.uRK looci, CORHSOI
FOUlV«LtNrE(ICI]Rr,CnRE)
COPHON AND DlfENSION FUR SIMULATION
COMMON /HO/ A9,«CRE,AHALDS,ANETYP,ANnHUN,ANORUT,ASNUPT,
1 A«SSIJN,ASSSON,ASr>UNK,AXl,AX2,AVl,AY2,B,CCL,CLKTM,
2 C01JRE,COLHK,COIMLK,COLTMZ,COMPAP,CONA,CONB,
1 UJNC.COMD.CflNF ,(,DNF , COSCOL (CORACR (COSLND,
* CHI WIS,CRUSi?,CSlmTC,CSTHR,CTS,DAYS,DFLDEP,DMTAVE,
5 OMIMAX,DMTMINIl)MT51G,DOLCnL(DnLRIG,Df)LTON,
4 HOI rs,OROPAr,OK()VRr,t)SLC,OW,EV£NT,FINOAy,
7 FlATNO,FLrLTM,,FXfFY,HISC12,HISCH(HISCl<.,
8 HISC22,HISC23,HISC2'1,HISC32,HISCJ3,H|SC3*,
'> HI S(.YLBR,PtR()N,PNOMU,PNDSIG,
PMhl L I,(wO,01 ,U?,0),0', ,U'>,06,Q7,U8,0'J,OlOt
U11,UMAX,OU,UUIAVE,QU1MAX,UUIMIN,OUISIG,
9 UUItMC,bUlTTM,UllT2lRlRGVMAX,KGVMIN(RICKA
COMMON /HI)/ R 1(,KH,R IGMiX,RI(,VFL,RK4,RKAA,RKH,RKBR,RKCC,
1 ROADIS,RMXDSH,RMXDST (RND,RUNNO, SCOLMl , SMWRKT ,
2 SRK.ML.STAT.ST.IF ST , STRFML , SUMKUT , SUHTRK ,
1 tARFA,THALOS,TIMF,TIMEO,TNETYP,TNOHUN(
4 TaNAr,E,TCITC(IS,TnrTON,TOTWT(TRC,TRCSIN,TRES,
5 rRfHR,TRFML,TRFTMi,TR[P,TRKOAY,TRKLD,TRL.
6 TRLHAL,IRPCl]L,rHPRlG(TRPTM,TSCOST,ISHR,
? I SI riPA,TS!M,TX,TY,UNACRE,UTILTY,VELMAX,
8 VtLMIN.VELMUR.VI LMUT , VEL SGR, VEL SGI , WA I E ,
9 WATE/.WT, XUAY.YRS
DIMENSION AHALDSI25)»ANETYPI25 I , ANOHUNI 25 I , ANORUT 1 25 )
1 ASNUPU25),AASSUNI?5I,AX1(25I .AX2I25)
2 AY1I25I (AY2I25I, B I 10 I , CCL ( 6 I , COLMl K ( <, )
1 CORACHKil ,CTS(6) .EVENTI60) .HISC12I16)
* H I SCI 31 161, H I SC 1M 16), HI SC 221 16), HI SC 231 16)
5 HlSC2M16>rHISC32U6),HISC33ll6>.HISC32(16),HlSC'mi6),HlSC'> I S t 25 ) , STAT I 90 )
DIMENSION TIPM60) ,TONAGE(6I ,TOTWTI50) ,TRCI60) .TRIPI9O)
1 TRKLUI50) .TRllhOI , T STMI 10001 , WATE I 501 ,
2 IMYS(2,3I, ITIMLI2.12), QUI T TM( 50,6 I , RKAAC.,21,
3 KKRBU,2>( RKCCCi,2),TARFAI50,3l,THALDSI50,31,
* 1IMrai2,l2). INI 1»P( 50.11, TNOHUNI50.3)
M A X T • 1 (J C n
MAXINf - ICOOOO
If.lif f K «fl
J( IM (,K all
0020
0030
0040
OOSO
OOfiO
0070
0080
0090
0100
0110
0120
0130
0140
0150
0160
01 70
0180
0190
0200
0210
0220
0230
0240
0250
0260
0270
0280
0290
0300
0310
0320
0330
0340
0350
0360
0370
0380
0390
0400
0410
0420
0430
0440
0450
0460
0470
0480
0490
0500
0510
0520
0530
0540
0550
0560
0570
0580
0590
0600
0610
0620
06 JO
O',40
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
XIN
-------
67
c
c
c
c
1 m s T H •= o
II Rtr^-n
ir «ii ? -o
irtni 1 1 1 -o
ICUHI 1 2 1 »0
ICUREI 3 )=C
MAXCRF « 1000
l(;VRHt>*4
ICAtDR*0
lC(JRFI4)"ll)VRHI)
ll;(IPM2»- 12 3456
IT)UHM4*-234t>67
J« ICVRH04 1
OE! 105 I'J,MAXC ME
105 1COHF 11)^0
J« P AXf H F- - 8
M] 104 I=IOVHHO,J,8
104 CALL F ILAS1 I 1,8, IFRST8I
HE IIJRN
EM)
»IBFTC ZFR1»
C
C
C
C
C
C
C
c
c
SUBROUTINE itRINt
COMMON AND RIMFNStON FOR LIST PROCESSING ROUTINES
CDMMUN IBUG, I CAl OR, I CHECK, 1C LOCK, 1 CORE , I DUMM2 , 1 DUMM4 , I FRST2
COMMON IFRST4,lERST8,IUVHHtJ,ITIMEl,ITIME2,IIYPE2,JBUG,JCHECK
CfjKMON MAXCRf»MAXINT,MAXT»lTYPEl
DIMENSION ICORK1000), COREI50I
t UU I VALENCE ( 1 CORF .CORE )
COMMON AND DIMENSION FOR SIMULATION
CflMMON /HO/ A9, ACKE,AHALnS,ANETYP,ANOHUN,ANORUT,ASNUPT,
1 AASSUN,ASS';UN,ASSUNK,AXI,AX2,AY1,AY2,B,CCL.CLKTM,
2 Cdt 1 RF,C()LHR,CULMLK.CQLTMZ,COMPAP,CC)NA,CONB,
3 tnNC,Cf)ND,U)NE,CnNF,COSCOL.CURACR,COSLND,
4 CREWTS,CRUSZ,CSHRTC,CSTHR,CTS,DAYS,DELDEP,DMTAVE,
5 UMTMAX.nMTMIN.OM T S 1 G , DOLCOL ,OOLR IG , OULTON,
6 00 L T S,DROPAY, OKI) VRT , OSLC ,OW,E VENT, FINDAY,
7 FLAtNU,FLrLrM,FX,FY,HISC12,HISC13,HISC14,
fl HlSr.2?.HlSC23,HISC24,HISC32,HISC33,MISC34,
9 H I SC42, H I SC 43, H I SC44
COMMON /BO/ HISTIlliHI STU1 , H I STU2 ,H I STU3 ,H 1 STU4,
1 1C 01 FR, IN.INCRMI , IOU> IRUNNOt ITIMLt JDWiJTRCt
2 JTRI,JIRPCI,JTRPRG,K,K2,K4,K5,KAPTS,KINTRK,
3 KlNrRL,KSTMFS,K1MDP,MAXLC,NA,NAREA,NC«NOA.
4 NDR,NN,NURUT,NOFLTS,NOTRC,NOTRC2,NOTRK,
5 NOTRL , NO VRT 1 ,NOVR T2 ,NOVR T 3 , NT ,ONCF ,OP TM,
« CJRHR,OVPAYL,OVRTM,PAYLBR,PERUN,PNDMU,PNDSIG,
7 PRHFl T, 00, 01, 02, U3, 04, 05, 06, 07,08,09,010,
B 011,QMAX,QO.UUIAVE.UUIMAX,OUIMIN,OUISIG,
9 QUlrMC,UUITTM,gur2,R,RGVMAX,RGVMIN,RIGKA
CC1PMON /BD/ RIOKB.RIGMAX.R 1 GVE L , RK A , RKAA, RKB.RKBB ,RKCC ,
1 ROAOIS.RMXDSR.RMXUSt ,RND,RUNNO, SCOLML , SMMRKT ,
2 SKICML, STAT.STMFST.STRFML.SUMRUT.SUHTRK,
3 lAKtA.THALOS.TIME, T 1 MEO , TNE T YP, TNOHUN,
4 TONAGF,TOTCnS,TOTTGN,TaTkT,TRC,TRCSIN,TRES,
5 THFHR,TRFML,TRFTHZ,TRIP,TRKDAY,TRKLU,TRL,
A TRLHAL,TRPCOL,TRPR|G,TRPTM, TSCOST.TSMR,
7 TUBPA,TSTM,rx,!Y,UNACRF,UTILTY,VELMAX,
8 V6LWIN,VELMUR,VELHUT,VELSGR,VELSGT,HATE,
9 WAIFZ.WT.XOAY.YRS
I) (PENSION AHALOSI25I , ANE T YP ( 25 1 , ANOHUNI 25 ) .ANORUTI25),
1 ASNUPT(25),AASSUN|25),AX1(25) .AX2I25) ,
2 AY1I25) .AY2I25), B I 10 ) ,CCL 1 6 1 .COLMLK ( 4 ) ,
3 CORACRI4I ,CTS(6) .EVENTI60I .H1SC12I16I,
4 H[SC13ll6)iHISCI4(16ltHISC22<16)tHISC23U6tt
5 HISC24I 16I.HISC32I 16I.H1SC33I 161 .HISC34116I,
» H1SC42(16I,HISC43I16I,H1SC44I16I,HISTD1I16),
7 HlStUl(16!,HlSTUJ(16>,HISTU3tl6l,HlSTU4<161,
8 OPTMI60I .OVRTMI50) .PERUNI4) ,00(501 ,
9 OUITMC(60I,CJUT2(300I,ROADIS(25»,STAT(90)
OlfFNSICN IIHEI60) .TONAGEI6) ,TOTWT(50) ,TRC(60I ,TRIP(90I
1 TRKLDI50I .TRLI60I , T STM I 1000 ) , HATE 1 50 ) ,
2 OAYSI2.3), IT1KLI2.12I, OUI T TM 1 50, 6 ) , RKAAI4.2),
3 RKRBI4.2), RKCC(4,2),TAREA(50,3I,THALDS( 50,31,
4 MMEU(2,12I. INFTYPI50.3I, TNOHUNI50.3I
DC 29 1 * 1,90
S* AT t 1 ) = 0.
TRIP II) « 0
29 CONTINUE
0650 XIN
0660 XIN
0670 XIN
0680 XIN
0690 XIN
0700 XIN
0710 XIN
0720 XIN
0730 XIN
0740 XIN
0750 XIN
0760 XIN
0770 XIN
07(10 XIN
0790 XIN
0800 XIN
0810 XIN
08?0 XIN
08 JO XIN
0840 XIN
0850 XIN
0860 XIN
0870 XIN
OBHO XIN
0010 ZER
0020 ZER
0050 ZER
0040 ZER
0050 ZER
0060 ZER
0070 ZER
0080 ZER
0090 ZER
0100 ZFR
01 10 ZER
0120 ZFR
0130 ZFR
0140 ZER
0150 ZER
0160 ZFR
0170 ZER
0180 ZER
0190 ZER
0200 ZER
0210 ZER
0220 ZER
0210 ZER
0240 ZFR
0250 ZER
0260 ZER
0270 ZER
0280 ZFR
0290 ZER
0300 ZER
0310 ZER
0320 ZER
0330 ZER
0340 ZER
0350 ZER
0360 ZER
0370 ZER
0380 ZER
OJ90 ZER
0400 ZER
0410 ZER
0420 ZER
0430 ZER
0440 ZER
0450 ZER
0460 ZER
0470 ZER
0480 ZER
0490 ZER
0500 ZER
0510 ZER
0520 ZER
0530 ZER
0540 ZER
, 0550 ZER
0560 ZER
0570 ZER
0580 ZER
0590 ZER
0600 ZER
0610 ZER
0620 ZER
0630 ZER
0640 ZER
0650 ZER
-------
68
HOO
771
m
111
12)
160
159
100
137
li( HOO 1
H < 1 1 - 0
r.flM INUI
Dt III I
S<«I (I 1 =
C(1N 1 INUF
or n? i
SIM ( 1 I '
I.OM INUI
i;( in i
cri 1 1 1 •
r. i s I I I '
Tl'NAf.F 1 1 I
rt M INUF
nil 12? i
ISTM 1 1 *
cr NI INuf
nn ivi i
F)l! 160 J
IIPFCJt 1 ,J
COM INUF
U M INUI
or 100
ASNUPTI )
AfULOSI 1
AASSUNI )
AM1RUTI 1
tLNl INUF
CCLHR = 0
rr.scuL >
OfTAVE -
UHTMAX *
DC IMIN »
DC T Sir, =
UI1I.CIIL '
1)01 KIR -
Dill. TON «
K2 " 0
K* * 0
K5 - 0.
HAXIU « 0
Nf = 0
f»N ' 0
NCFLTS =
NCIHK
NdVKIl >
N(!VRT2 »
NIJVRT3 *
URHR - 0
DO - 0
01 * 0
U2 ' 0
UTH = 0
OUIAVE -
GUI MAX '
CUIMIN -
uu i sir, '
SCOIML =
SMhRKT *
SRIGML •
SIATI M )
STRfPL *
SUMRUT »
T01COS '
TOHDN «
1RCSIN »
IRfHH • C
IRKHAY *
THPCOL •
TBPHir, "
T^(.(]ST •
lit'R » 0
IT T « 0
ITI2 - 0
X . 0
XI 3 • 0.
1*0
ICOIFR *
IRIINNO *
DP 137 1
QUT2I 1 ) '
CCNT INUE
• 1 , 10
•• 5I.NOTRC?
N
» 7/.90
10
• 1,6
0
0
- 0
' 1,1000
0
• 1,?
• 1.12
l»0.
k l.NAREA
- 0.
• 0.
* 0.
- 0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0
0.
» 13
0.
0.
0.
0.
0
0.
0.
0.
0.
COI.FRE
RUNNO
• 1,300
0
nr 55 i = 1,50
06(»0 ^tR
0670 IfK
0680 /ER
0690 ZER
0700 It*
0710 JER
0720 HH
0730 IIR
07*0 UK
0750 liH
0760 *ER
0770 ZER
0780 ZER
O7'»0 /ER
0800 /FR
OBIO ZER
OB20 ZER
08)0 ZER
OH'.0 ZER
OB50 ZFR
OHM) ZER
0870 ZER
OBHO ZEH
O8'*0 ZER
0900 ZER
0910 ZER
0920 ZER
0930 ZER
O'MO ZFR
0950 ZER
0960 ZER
0970 ZER
0980 ZER
0990 ZER
1000 ZER
1010 ZER
1020 ZER
1030 ItR
1040 ZER
1050 ZER
1060 ZER
1070 ZER
1080 ZER
1090 ZER
1100 ZER
1110 ZER
1120 ZER
1UO Z6R
11*0 ZER
1150 ZFR
1160 ZER
1170 ZtR
1180 ZER
1190 ZER
1200 ZER
1210 ZER
1220 ZFR
1230 ItK
12*0 ZFR
1250 ZFR
1260 ZER
1270 ZER
1280 ZER
1290 ZER
1300 ZER
1310 *ER
1320 /ER
1330 ZER
13*0 ZER
1350 ZFR
1360 ZER
1370 ZFR
1380 ZEF)
1390 ZER
1*00 ZER
1*10 ZER
1*20 ZER
1*30 ZER
l**0 ZFR
1*50 ZFR
1*60 ZER
1*70 ZFR
1*HO ZER
1*90 ZER
1500 ZER
1510 ZER
1520 ZER
1530 ZER
15*0 ZER
1550 ZER
1560 ZER
1570 ZER
-------
Ul, 56 J * l(6
QUITTM I.J) " 0.
56 CONTINUE
55 CONTINUE
100
100
00 200 t
CO 300 J
TARFA I 1
INOHUNI I
TH»LDS( 1
TNFTYPt I
U1NUNUE
CONTINUE
RFTURN
FND
« 1
« 1
.J)
.J)
.J)
• J)
50
3
0
0
0
0
1580 ItR
1590 Iff.
1600 Iff.
1610 I If.
1620 ZER
1630 £ER
1650 HR
1660 ltH
1670 ZER
1680 ZER
1690 iER
1700 ZER
1710 ZER
1720 ZER
1730 ZER
-------
Environmental Protection Agency
Library, K;vy:nr V
1 North ',7iV:~:cr j,-i.;vo
Chicago, Illinois 60606
------- |