EPA-670/5-73-12
July 1973
iocioeconomic Environmental Studies
SYSTEMS SIMULATION AND
SOLID WASTE PLANNING
A Case Study
National Environmental Research Center
Office of Research and Development
U.S.Environmental Protection Agency
Cincinnati.Ohio 45268
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EPA-670/5-73-12
July 1973
SYSTEMS SIMULATION AND SOLID WASTE PLANNING:
A CASE STUDY
Robert M. Clark
and
James I. Gillean
Program Element 1D2065
National Environmental Research Center
Office of Research and Development
Environmental Protection Agency
Cincinnati, Ohio 45268
-------
REVIEW NOTICE
The National Environmental Research Center,
U. S. Environmental Protection Agency, has
reviewed this report and approved its
publication.
11
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FOREWORD
Man and his environment must be protected from the
adverse effects of pesticides, radiation, noise and other
i'orms of pollution, and the unwise management of solid
waste. Efforts to protect the environment require a
focus that recognizes the interplay between the com-
ponents of our physical environment — air, water, and
land. The National Environmental Research Centers
provide this multidisciplinary focus through programs
engaged in
• studies on the effects of environmental
contaminants on man and the biosphere, and
• a search for ways to prevent contamin-
ation and to recycle valuable resources.
This publication of the National Environmental
Research Center, Cincinnati, reports on work related
to the application of systems analysis techniques to
urban solid waste management. These techniques when
properly applied can be powerful tools for bringing
difficult environmental management problems under
control. The work cited in this publication illustrates
the successful application of the systems approach to
solid waste management in Cleveland, Ohio.
A. W. Breidenbach, Ph.D.
Director
National Environmental
Research Center, Cincinnati
ni
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ABSTRACT
Adequate solid waste management planning is one
of the major problems facing most medium-to-large
urban communities in the United States. Increasing
waste generation, difficulties in labor-management re-
lations, decreasing land resources, increasing effluent
standards, rising cost, and uncertain technology are
only a few of the problems facing today's solid waste
managers.
A technique which is ofte'n suggested as a means of
bringing these kinds of problems under control is the
so called "systems approach." This phrase as generally
used is often vaguely defined and is many times totally
meaningless. The work cited in this report is a success-
ful application of systems analysis to solid waste man-
agement problems in Cleveland, Ohio, and is intended to
illustrate the power of the "systems approach" when
properly applied. It is hoped that the work cited in
this report will be helpful to other communities in the
solution of their solid waste management problems.
IV
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SYSTEMS SIMULATION AND ITS APPLICATION
TO SOLID WASTE PLANNING
A CASE STUDY
by
1 2
Robert M. Clark and James I. Gillean
INTRODUCTION
Adequate solid waste management planning is
one of the major problems facing most medium-to-
large urban communities in the United States. In-
creasing waste generation, difficulties in labor-
management relations, decreasing land resources,
increasing effluent standards, rising costs, and
uncertain technology are only a few of the problems
facing today's solid waste managers.
A number of analytical tools, including manage-
ment information systems, simulation, and mathemat-
ical models, are available that can be applied to
solve these and related problems.
Many studies have explored the application of
deterministic and simulation modeling to urban solid
waste management problems (4)(7). Several recent
papers have applied these techniques to routing and
1. Sanitary Engineer, Office of Program Coordination,
National Environmental Research Center, U. S. Environ-
mental Protection Agency, Cincinnati, Ohio 45268.
2. President, ACT Systems, Inc., 807 West Morse Boule-
vard, Suite 200, Winter Park, Florida 32789
-------
facility location with the use of either assumed
data or data collected on a one-time basis (2) (5) (6).
These approaches have been useful for demonstrating
the potential of "systems" or operations research
techniques for assisting the solid waste manager in
making important operational decisions. None of the
studies, however, have considered the problem of ob-
taining continuous data and utilizing it, together
with mathematical models, for making "on-line" deci-
sions. This paper reports on the results of a pro-
ject in Cleveland, Ohio, in which reliable, uniform,
and continuous data collection is combined with a
dynamic simulation model to form a system for making
short- and long-term management decisions. A system
composed of five basic components has been establish-
ed:
1. A mechanism for the collection of con-
tinuous, uniform, and reliable data on
the solid waste management operation;
2. An analysis of the variables that have
a significant effect on the solid waste
system, such as present and expected
changes in population trends and dis-
tribution, and changes in transportation
systems;
3. A simulation or resource allocation
model using the continuous data as
input and incorporating variables that
significantly affect the system;
4. A mechanism for exercising the model
and utilizing its results for making
immediate or long-range decisions; and,
5. The capability to compare the models'
predictions with continuous data.
As a result of the system's implementation, the
city has taken several steps to bring Cleveland's
solid waste management problems under control. They
have
1. Reduced service from back yard to curb side;
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2. Developed an on-line management informa-
tion system;
3. Developed a simulation model for short-
and long-term planning purposes;
4. Reduced the number of routes from 224
to 138;
5. Developed a plan for short- and long-
term capital investment for collection
and disposal; and,
6. Investigated new disposal alternatives
for the city's waste.
By implementing the project's recommendations, they
have saved $9 million in 2 years. This represents a
change from over $14 million, when the project was
initiated, to a current budget of approximately $9
million. To understand the problems and successes
associated with this effort, it is necessary to know
something of the history and political climate that
influenced the development of the system.
THE SITUATION IN CLEVELAND
In most large American cities, the population
is reluctant to vote for additional taxes and yet
either demands more services or refuses to relinquish
the services they already have. Faced with demands
for higher wages as well as increases in the purchase
price of equipment, facilities, and other non-labor-
related items, many cities have an eroding tax base.
As middle- and upper-income families move to the
suburbs taking with them needed tax revenue, lower-
income families who produce less tax revenue but who
require just as many services take their place. The
condemnation of property for highways and other non-
taxable uses also reduces potential income for the city.
A similar situation developed in Cleveland. This,
coupled with the defeat of a much-needed tax levy,
created a financial impact felt in all city departments;
nowhere was the impact more acute than in the department
responsible for the collection and disposal of solid
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waste. The City of Cleveland's Division of Waste
Collection and Disposal was moving waste from the
point of generation, transporting it to the disposal
point, and disposing of it with no effort required
by the general citizenry.
Shortly before this financial crisis, however,
the city initiated a cooperative program with the
U. S. Environmental Protection Agency (EPA) in which
data from Cleveland were used as a source for a
national solid waste data network. Working with the
Division of Waste Collection and Disposal, EPA began
collecting data on a regular basis in October 1970(3).
Two routes were selected for continuous evaluation,
and data were obtained from the collection vehicle
operator on each route in the form of daily reports.
The Commissioner of the Waste Collection and
Disposal Division, faced with a number of difficult
decisions regarding possible reductions in service
levels, was able to use several months worth of data
available from the two routes being monitored within
the city. Their six-man crews giving back-yard, once-
per-week service could be compared with other systems using
the two routes being evaluated within the EPA pilot network,
After careful review of the preliminary monitor-
ing data for these sample routes, back-yard service
was eliminated and the collection crew was reduced by
two men, leaving one driver and three laborers.
Several months later, the crew was reduced to two
laborers. Data collected on both routes from October
1970 through May 1971 are shown in Table 1. On these
two routes, the cost per ton for waste collected for
an average day dropped from close to $30.00 to approxi-
mately $13.00, with an estimated annual savings of over
$4 million per year.
These national network data proved so valuable
that a project was initiated to collect similar data
from all of the city's routes. The city using an EPA
local and regional planning grant developed an on-line
solid waste management information system (1).
DATA SYSTEM DEVELOPMENT
To develop the information system properly, the
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TABLE 1. COLLECTION COSTS (in dollars) FOR TWO SAMPLE ROUTES
Month
1970
to
1971
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
Oct.
Nov.
Oec.
Jan.
Feb.
liar.
Anr.
May
Crew
size
6
6
6
4
4
4
3
3
6
6
6
4
4
4
3
3
Equipment
cost/day
18.64
16.69
20.72
19.72
22.16
19.13
24.85
23.85
27.32
25.15
34.07
37.57
37.42
39.12
37.62
29.12
Manpower
cost/day
Route
194.88
194.88
194.88
130.56
130.56
130.56
98.48
98.88
Route
194.88
194.88
194.88
130.56
130.56
130.56
98.48
98.88
Total
cost/day
No. 1
213.52
211.57
215.60
150.28
152.72
149.69
115.33
123.73
No. 2
222.20
220.03
228.95
168.13
167.98
169.68
128.10
128.00
Cost/ton
30.30
36.50
34.81
22.50
20.40
20.19
14.50
14.14
26.10
26.19
27.00
16.60
17.00
15.21
11.28
12.64
Weekly cost/
residence
served
.499
.494
.501
.351
.356
.350
.270
.289
1.011
1.005
1.041
.765
.763
.771
.583
.581
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organization and management of the Division of Waste
Collection and Disposal was completely analyzed.
After the organizational study was completed, the data
system was designed and implemented.
Organizational Study
The Division, whose purpose is to provide service
to slightly less than 250,000 family units, is composed
of personnel, vehicles, and facilities. The Commissioner
in charge of the Division supervises six station super-
intendents with subordinate foremen as shown in Figure 1.
There is no preassigned number of foremen in each
station: station 100 has three foremen, whereas station
400 has six foremen. Each foreman is responsible for
collecting waste from the routes assigned to him.
Figure 2 shows the general organization of station 100;
as indicated, each foreman may supervise a different
number of crews (i.e., foreman 110 supervises three
crews, whereas foreman 130 supervises five crews).
The collection crew is usually composed of a driver
and two waste collectors who, upon arrival at the route,
work until the vehicle is filled to capacity or until
the day's effort is completed. If the vehicle is filled
before the route is completed, the driver takes the load
to the disposal point and returns to the route. Upon
completion of the route, the driver unloads at the city's
incinerator if he has a partial load, or at a private
landfill if he has a full load and has time remaining in
the working day to make the round trip. On some occa-
sions, he is instructed to return to the motor pool with
the partial load if time becomes a critical factor.
As part of the organization study, numerous
interviews were conducted with the staff of the
Division. Employee records were searched for data
pertinent to systems operations: e.g., unexcused
absences and collector's age. (The average age of
the waste collectors was 49.2 years, which seems
high when compared to other similar occupations.)
Cost data was collected on use and maintenance of
vehicles and on facilities and equipment for main-
tenance. Examples of some of the maintenance data
acquired in the study are shown in Figure 3.
-------
COMMISSIONER
STATIONS
Figure 1
Organization of Division of Waste Collection
and Disposal, Cleveland, Ohio.
-------
100
FOREMEN
110 120
111 121
112 122
113 123
124
130
131
132
133
134
135
Figure 2
Organization of One of Six Stations Within
the Cleveland, Ohio, Division of Waste
Collection and Disposal.
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o
o
o
1
—I
O
Q
70
60
50
40
30
20
10
1971
Figure 3
Vehicle Maintenance Costs.
-------
This information provided important background
data for development of the management information
system. As part of the system development, the
outputs needed to satisfy management requirements
were determined. After the output requirements were
specified, input data to produce the required out-
puts were identified. A data processing system was
developed, and the management information system was
implemented.
Output Requirements
Thorough review management requirements indi-
cated three general data information categories for
output requirements: route, collection, and cost.
The types of information generated by the system
are shown in Figure 4. Information from each route
foreman and station is computed on a daily average
for a week. In addition to the daily averages, the
foreman or station may sum the values related to the
routes where deemed meaningful.
Critical data from each station's report are con-
solidated to provide the weekly commissioner's report
with sums and daily averages for the over-all daily
collection. In addition to the tabulated information,
certain exceptional information for the five highest
routes and the five lowest routes is printed out for:
® Average weight collected per day;
e Average time spent collecting per day;
« Homes served per collection crew;
« Collection time per home;
e Collection time per 100 pounds;
© Working time to paid time;
0 Incentive cost per day;
® Cost per ton; and,
« Cost per home per week.
10
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CLEVELAND
DIVISION Of CClLCCIlON ANU DISPOSAL
HOUTt ]NfO«MAII UN
t OU' f
f. l/Nftf R
Ml.
012.
0»»!>
Of
DAIA USFO
3.
«V£I-«CE
vtwIClf
ICU YDI
20.
VEHICLE
:t
^* • •.!.•" ~ '^-V
MOT OK POOL
TO aoim
(PfR OAV)
l«ILtS»« (MINI
<..$ 2C.7
2.7 21. C
COLLf CT ION
QPERAT to
(?£(• OAtr)
(MILESt* (HINt
<-.C 226.7
TRANSPORT
OPERATION
..U«l. I.IHI
15.5 9b.o
n.o i?2.o
xEICHt
;?£
CLEVELAND
DIVISION Of COLLECTION AND DISPOSAL
till.
01 2.
SIRvEO
COll(C<
<.3>)
?86.
Pt»
PER
COLIEC1
(POUNDS 1
47.0
74. Q
SERVED
COILEC1
1410.
919.
Pt*
0«v
(POUNDS)
2.1
1.3
(MINI
O.J2
0.1,1
I IKE
(H1N1
1. 10
0.92
COLLECT
I1H£ TO
1 1 ML
( Mf HI
0.<>t>
O.Sft
* AC1UAL
TfHC TO
1 1«£
(MINI
0.72
0.71
LOADS P£« WEEK • uE IGhl
* P(R
IhClN • LAND • JtffR MSI LflAO
* f-ILL * S'A *( POUNDS)
» * •
0. *>. 0. 621.
6. 3. 0. 66*..
.
M 1.
^h r - _ — •
fcOUTt * COLL ECT *
6.C4 88.16
CLEVEIANO
DIVISION Lit COLLECTION AND DISPOSAL
tOSI INFORM AT (ON
(OOLLAttS)
» 10TAL » TOt*L • •
XPQRI • COST • COST • COSt * COST
• » » »
37.34 35.8^ <»7.ti8 133. S3 27. dl
«.i.t»3 «.1.6I *". *fl M«.?« 12.87
COST COST COST
LOAD ION MOHE
30. 12 12.93 0.30
S' .7? 1C.C6 0.^3
w^-^— — ^*~~*~- — —
COST
PERSON
WEEK
0.09
0.13
— - — -|M|| Mi , __, ,, ._,, ^,--
Figure 4
Computer Printouts Indicating the Types of
Cost, Collection, and Route Information
Gathered for the Solid Waste Management
Pilot Study.
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Input Requirements
When the specified outputs were precisely
established, the inputs needed to produce them were
determined. Forms were developed to log the neces-
sary data that would become the major inputs to the
system. Figure 5 illustrates the forms used to collect
information relating to vehicle identification and
maintenance, crew size, number of homes served, dis-
charge point, and other critical data. The data
system was developed so that data could be key punched
directly from the daily collection forms. The flow
of data into the system and resulting outputs are
shown in Figure 6.
System Implementation
In September 1971, as the data collection system
was implemented (except for the computer program), in-
consistencies and errors were logged so that corrective
action could be initiated. The data were then trans-
cribed to cards, checked, and run through a debugging
process.
In November 1971, the total implementation of the
system was completed including installation of the com-
puter program in the City of Cleveland's Data Process-
ing Center.
NONSOLID WASTE INFLUENCES
An attempt was made to define all of those non-
solid waste factors that have an impact on the solid
waste management function. For example, population
trends and densities and dwelling unit densities have
a significant impact. Transportation networks, in-
cluding changes in street mileages and the location of
major arteries and expressways, must be considered.
On-going or planned urban renewal projects have a sig-
nificant impact on population (location, numbers, and
densities) and, therefore, are significant for solid
waste planning. State laws and city and county ordi-
nances have a potential impact on solid waste manage-
ment. Some of these statistics for Cleveland are:
12
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ROUTE
DAILY COLLECJION ROUTE INFORMATION
DATE CREW
VEHICLE: NO.
NO. HOMES SERVED.
SIZE.
.FUEL(GAL).
.OIL(QT).
LEAVE MOTOR POOL
START COLLECTION
LEAVE ROUTE FOR DISCHARGE POINT
AT DISCHARGE POINT
ARRIVE BACK ON ROUTE
LEAVE ROUTE FOR DISCHARGE POINT
AT DISCHARGE POINT
ARRIVE BACK ON ROUTE
LEAVE ROUTE FOR DISCHARGE
AT DISCHARGE POINT
RETURN TO MOTOR POOL
TIME
MILES
WEIGHT
DISCHARGE
POINT *
-..
LUNCH-START (LEAVE ROUTE)
-FINISH (ARRIVE ROUTE)
MAINTENANCE-START
-FINISH
MAINTENANCE-PROBLEM
(Circle Number)
1 Brokei, wheels, llret
4 Fuel l»i
5 Pocket
6 Power or steering lyj
7 Olh.r
'ENTER NUMBER
1-INCINERATOR
2-LANDFILL
3-TRANSFER
REMARKS:
Figure 5
Sample Daily Data Collection Form Completed
by Collection Vehicle Operator.
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ROUTE INFORMATION
FORMS
JOB CONTROL
CARDS
PUNCHED DATA
I
DATA CARD
DATA CARD
SORTED DATA
SOURCE DECK
PROCESS
REPORTS
Figure 6 Management Information System Flow Chart
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Population 648,082
Dwelling units 212,486
Persons/dwelling unit 3.05
Land area (square mile) 67.52
Population density
(population/square mile) 9,598
Dwelling unit density 3,147
Miles of streets (collection/week)... 3319.5
Dwelling units/mile of collection.... 64.0
Demographic Profile
Demography is the science of population movement
and trends, and since the location of people has an
important impact on the solid waste management func-
tion, demography is, important to solid waste manage-
ment. The population of Cleveland that was over
900,000 in 1950 has declined steadily to approximate-
ly 750,000 in 1970 (Figure 7). It is expected to
stabilize at 740,000 over the next 20- to 30-year
period. Figure 8 shows family distribution by stations
in 1970. Interestingly, there appears to be a natural
division of the city into two components. Stations 200,
300, and 400 on the east, and stations 500 and 600 on
the west, contain the majority of the solid waste
sources.
Numerous changes are proposed in the transporta-
tion network for the city. Figure 9 shows the existing
major arteries and some proposed highways, and Figure 10
shows new urban renewal and neighborhood development
areas that will have an impact on the solid waste man-
agement function.
As part of the background study of Cleveland, the
city, county, and state ordinances, regulations, and
laws affecting solid waste were searched. The one county
regulation concerned disposal. Three of the state laws
concerned rules and enforcement and seven concerned dis-
posal. Of the 42 city ordinances and regulations, 12
concerned rules and enforcement; 6, containers; 6,
vehicles; 11, disposing; 1, charges, and 6, miscella-
neous subjects.
The demographic, transportation and neighborhood
development data were compiled along with data from the
management information system to provide the following
input information for the simulation model:
15
-------
950
900
850
800
750
700
le—•
1950 1960
1970 1980
YEARS
1990 2000
Figure 7
Population Trends for Cleveland, Ohio.
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Figure 8
STATION 400 (58,809)
STATION 200 (45,093)
\
STATION 100 (24,609)
STATION 600 (43,919)
STATION 500
(34,991)
STATION 300 (48,581)
Distribution of Families Within Each oi the
Six Waste Collection Subdivisions in
Cleveland, Ohio, October 1970. Each dot (.)
Represents 100 Households.
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Legend:
PROPOSED
EXISTING OR
COMMITTED
Figure 9
Major Transportation Arteries, Cleveland,
Ohio.
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MODEL CITY DEVELOPMENT
(Residential Rehabilitation)
• SPECIFIC PROJECTS
Erievie w
E. Woodland
GENERAL NEIGHBORHOOD University/Euclid^
DEVELOPMENT PROGRAM
LEE & SEVILLE
LOW INCOME RESIDENTIAL
Fig'jre 10
Urban Renewal Projects in Cleveland, Ohio.
-------
Generation data, composed of population,
dwelling unit, density, weight, and cost
information;
Collection data, including distances,
volume, pickup time, route identifica-
tion, vehicle type, and crew size and
costs;
Transport data, related to distance, time,
and speeds; and,
Disposal data, such as distance traveled,
offload time, disposal site, and related
costs.
MODEL DEVELOPMENT
The model consists of five master programs each of
which corresponds to the basic operation in the solid
waste collection and disposal activity: input data
logic, truck generation logic, collection logic, trans-
portation logic, and disposal logic. In a flow diagram,
the way in which the model simulates the system is
illustrated (Figure 11).
The input data consist of the basic statistics
that describe the system. For example, solid waste
generated, truck size, crew size, number of homes served,
collection time, and transport miles are all input data
to the model and are, therefore, fixed for each simula-
tion run. The values for each of these categories may
change depending on the type of collection system being
modeled.
The model then indicates the number of trucks
needed each day to collect the solid waste; this number
is based on the number of routes being considered, which
in turn, is based on the assumed amount of solid waste
generated per day. An 8-hour working day was used as
the base line for comparing various types of collection
systems. When the complete cycle of collection and
disposal was considered, however, a week's effort was
used for evaluating the various alternatives.
The collection logic assumes a set of work rules
20
-------
Figure 11
Flow Diagram of Model Logic Simulating- Basic
Operation of the Cleveland, Ohio, Solid Waste
Collection and Disposal Activity.
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and contains the supporting data to be used for a
specified collection system. For example, when a
two-man collection system, which consists of a
truck, a driver, and a helper, is being considered,
the assumptions are: that the driver will assist
the helper for approximately 60 percent of the time
spent collecting on the route; that, for this assistance,
the driver receives a wage adjustment; that, the
collection rate in the model varies from 1.1 pounds
per second per man to 2.5 pounds per second per man;
and that the walking rate for the collectors between
pickup point was assumed as 2 feet per second.
When a truck has been filled to capacity, it
enters the transportation logic routine. This rou-
tine assigns a disposal point and an associated
transportation distance to the truck based on its
position on the route when the collection task is
completed.
When a truck has made its trip to the disposal
or unloading point, the vehicle enters the disposal
logic routine. At the offload point, the truck is
assigned to an unloading lane where it may enter a
queue or unload immediately depending on the condi-
tions at the offload point. After the vehicles are
empty, their return to the motor pool or to the
collection route depends on their having completed
their assigned service routes, or on the time of day,
or on both.
The routines were used to model the performance
of an individual truck and crew as well as the per-
formance of the entire system. The first step in
the modeling process was to assume a three-man crew
and a rear-loading packer collecting over a typical
route using the collection logic. Various dwelling
densities were assumed, and a long-and a short-haul
option were considered. The long-haul option was
rejected as a reasonable alternative for Cleveland.
Next, the collection logic was used to test various
collection systems until several good ones were
found. The disposal logic was used to test the good
collection systems to determine various transfer
station configurations. Once these configurations
were determined, the truck generation logic was used
to estimate the required fleet size for the entire
22
-------
cit'y. This procedure was followed with the numerous
variations in the input data.
Programming and Validation
A General Purpose Simulation System (GPSS)
Language, Version V, was used to program the model.
Input data and work rules reflected current operations
in Cleveland.
For purposes of validating the model, the current
system was simulated with the use of input data that
describe the present operation. Results from the
model are compared with data collected from the man-
agement information system (Table 2). Output data
from the model include : (1) volume and/or weight
of solid waste handled; (2) miles traveled; (3)
collection times; (4) travel time; (5) weight handled
by each disposal point; (6) queueing conditions at
offload ramps; and, (7) number of homes collected.
SYSTEM EVALUATION
After the model had been conceptualized, pro-
grammed, and validated, it was used to evaluate various
alternatives that might be considered for current and
future use in the City of Cleveland. Part of this
effort was devoted to modifications to the present
system that might make it a more efficient operation.
Collection System Evaluation
Various collection configurations were evaluated
during the course of this study. Figure 12 shows a
schematic diagram of some of the alternatives that were
considered. For each collection configuration, the
effects of dwelling unit density, pickup location,
generation rate, vehicle size, and crew size were
evaluated. For example, the effectiveness of a scooter
system with a two-man crew, serving dense multi-family
dwellings was compared with a mother truck with a
satellite vehicle (M/ST), using a two-man crew, serv-
ing a low-density single-family home neighborhood with
normal generation rates. Each of the alternatives
shown in the schematic diagram was considered under
23
-------
TABLE 2.
SIMULATION OUTPUT COMPARED WITH COLLECTED DATA FOR STATION 100
Simulated data
Route No. (Ib collected/day)
111
112
113
121
122
123
124
131
132
133
134
135*
*Route information
12,
14,
7,
9,
13,
20,
19,
17,
22,
22,
21,
-
not
984
252
680
660
483
045
222
955
800
108
509
-
usable.
Collected data
(Ib collected/day)
12,
13,
7 ,
9,
13,
19,
18,
17,
23,
22,
20,
-
606
968
404
583
547
750
956
968
548
314
836
-
Percent
difference
3
2
3
0
0
1
1
0
3
0
3
.0
.0
.7
.8
.5
.5
. 4
.1
.2
.9
.2
--
24
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SYSTEM MATRIX
Service Conditions
DENSE MULTI-DWELLING
DENSE SINGLE-DWELLING
THIN SINGLE DWELLINGS
ALLEY COLLECTION
Generation Rafe Collection Systems Crew Size
NORMAL
GENER-
ATION
SCOOTER
JESTING CONDITIONS
1 MAN
2 MAN
3 MAN
4 MAN
SHORT HAUL (8 Ml)
LONG HAUL (40 MIJ-yPRESENT
/ (1 WK)
FOR
1 ROUTE
$ TON I COST EFFECTIVE SYSTEMS
FOR SPECIFIC CONDITIONS.
$ RESIDENT \ THIS MAY BE SEVERAL
8-10 SYSTEMS
Figure 12
Schematic of Alternative Collection Configurations
Considered.
-------
long-haul (40 miles) and short-haul (8 miles)
conditions when serving one route with once-per-
week collection. Immediately this analysis showed
the short-haul situation was far superior for all
of the alternatives considered. The ratio of the
total weight collected with a short haul to total
weight collected with long haul is approximately
two to one. With these results, the long-haul
alternative was eliminated from future considera-
tion.
The criteria used to rate each of the systems
were: (1) ratio of pickup time to transport time;
(2) dollar per ton; (3) dollar per residence; and,
(4) "optimum termination point." The first three
items are self-explanatory, and the final item is
defined as the physical point at which the collec-
tion .effort terminated in an 8-hour working day.
Highest ratings were given to the vehicle/crew
combinations that could complete the work load in
an 8-hour day. The best system was assigned a rank
of one, the next best system two, and so on. Table
3 summarizes the rankings achieved by the various
systems considered.
The 29-yard truck with a 2-man crew (29-2), and
the 10-yard truck with a 1-man crew (10-1) had the
best performance capability. This choice was made
under average conditions for waste generation. To
test the capacity of these two alternatives for
collecting under extreme conditions, a peak genera-
tion day was assumed. After routes were restructured
and brought within optimum length, simulation runs
were made under maximum generation conditions.
Another test was made to see if these two collec-
tion systems together could accomplish the service
responsibility better than either system alone. The
29-yard truck was assigned the task of collecting
dense multi-family dwellings, and the 10-yard truck
was given sparsely-settled areas. This combined
system proved to be efficient but no more efficient
than either system alone.
Based on several subjective considerations, the
29-2 configuration was declared optimum. The 29-yard
truck with a 2-man crew allows for more flexibility
26
-------
TABLE 3.
COMPARISON OF COLLECTION PATTERNS,
RATING VARIOUS VEHICLE AND CREW SIZES
Ranking
or system
1
2
3
4
5
6
7
8
9
10
11
12
Vehicle and
crew size
(configurations)
10-1
29-2
16-1
29-3
20-2
10-2
M/ST-L
20-3
29-4
16-2
M/ST-2
16-3
Negative
points accrued
50
66
81
83
88
101
115
120
123
130
141
150
27
-------
than a 10-1 system. Union rules and safety require-
ments are more consistent with a 29-2 system than
with a 10-1 system.
Offloading Site Evaluation
After the most efficient collecting system had
been identified, an evaluation was made to determine
the best offloading sites. A schematic diagram out-
lines the variables considered in this determina-
tion (Figure 13).
The topography of the Cleveland area dictated
the possibility of dividing the city into two general
route groups: the area currently in stations 500, 600,
and the western part of station 100; and the area
currently in stations 200, 300, 400, and the eastern
part of station 100 (Figure 8).
The western district developed favorably into a
36-route configuration, offloading at the Ridge Road
landfill, and the eastern district, into a 53-route,
offloading at a landfill at 34th and Broadway (due
east of the West 3rd facility and halfway into the
district) (Figure 14). At this time, it was deter-
mined that a motor pool would be located at both
landfills to eliminate travel time after the last
offload. The constraints on the simulation runs
were: (1) the truck must make at least one but no
more than two offload trips; (2) collections must be
made at a peak generation period; (3) the number of
homes must be a maximum; and (4) the task must be
accomplished with a 40-hour work week, with 1.5 to
2.0 hours remaining on the fifth day for general
truck maintenance, and a 0.5-hour period remaining
on each of the other 4 days to wash the trucks.
Simulation runs were made with the use of the 29-2
truck/crew configuration and with pickup times
varied from 36 to 52 seconds. The number of homes
to be serviced was set at 83,016 in the western
district and at 129,470 in the eastern district.
The results of these runs were within the frame-
work of the conditions stated above.
Another variation was examined in which the off-
load destination was changed from 34th and Broadway
to the Garden Valley site 2 miles northeast of the
28
-------
ENTIRE CITY
-NORMAL GENERATION-
COMBINED SYSTEM
TRANSFER
STATION CONF. NO. 2
8 HR. WK. DA
7 HR. WK. DAY
Figure 13
DATA SYSTEM
S TON
S RESIDENT
10UEUEING
GRAPHS
ETC.
Matrix Indicating Variables Considered When
Determining the Best Unloading Sites.
PLAN
OF
ACTION
-------
1
2
3
4
5
6
7
8
24th & Rockwell
West 3rd St.
49th & Harvard
Glenville
Ridge Rd. West
Ridge Road East
Ridge Rd. Landfill
Vehicle Main Shop
Figure 14
Locating City-owned Property Used by the Cleveland
Division of Waste Collection and Disposal.
-------
49th nnd Harvard facility (Figure 14). This change
naturally constituted a variation in total transport
miles; however, the model indicated that the variation
was not significant. Again, the results were positive,
falling well within the required conditions previously
stated.
Careful consideration indicated the best off-
loading configuration would be to use the Rockside
landfill as a terminal and disposal point for the
proposed westside division and the Garden Valley site
as a terminal and transfer station for the eastside
division. The waste would be transported in vans
from Garden Valley to the Rockside landfill for final
disposal.
Entire City Evaluation
A schematic diagram illustrates variables for
the simulation model for the entire city (Figure 15).
To check the results of the model, the 92-route con-
figuration, with the 29-2 configuration and the most
efficient disposal alternatives, were simulated.
The simulation results indicate that this total con-
figuration could easily handle the city's solid waste
problem.
STUDY RESULTS
The results of the simulation study combined
with the management information system have been
spectacular. In 1970, the total complement of em-
ployees of the Cleveland Waste Collection and Dis-
posal Division reached a maximum of 1,825. With
the use of data obtained in EPA's pilot data network,
the number of personnel actually collecting waste on
the route was reduced 50 percent. Service in collec-
tion operations was changed from back yard to curb
side .
After the management information system and
simulation model were developed, the total number of
routes was reduced from 224 to 138. The total per-
sonnel complement now numbers approximately 600 em-
ployees. The annual budget has declined from $14.3
million to approximately $9.0 million in 1972.
31
-------
ENTIRE CITY
COMBINATION SYSTEM-
PURE SYSTEM NO.1-
PURE SYSTEM NO. 2
TRANSFER STATION CONF, NO. 1
" NO. 2J
" NO. 3
[PRESENT
J5 YR (1 H.-
M5 YR (1 W6£X)J
Figure 15
OATASYSTEM-
COST EFFECTIVE SYSTEM FOR THE CITY.
Matrix Indicating Variables Considered for
Simulation of City-wide Collection and
Disposal System.
-------
The simulation model has been used for both
short-term and long-term analysis. In the short term,
it was used to restructure existing routes to achieve
the budget reduction. In the long term, it has been
used to develop the following solid waste management
plan:
» The city will be broken into two divisions
for solid waste collection. These two
divisions are identified as the Westside
District (identified numerically as 100)
and the Eastside District (identified
numerically as 200) .
-------
PERSONNEL
INITIATED CURB PICKUP WITH 4 MAN CREW
CURB PICKUP WITH 3 MAN CREW
CURB PICKUP WITH 2 MAN CREW
ROUTES
SW DIVISION ESTIMATE
FUNCTIONAL VEHICLES
70 75 80 85
YEAR
Figure 16
Projected Changes in Personnel, Routes, and
Functional Vehicles for the City of Cleveland
-------
POPULATION
(thousands of people)
800
700 I-
500
400
300
200
GENERATION
(thousands of tons)
BUDGET
(m illions of dollars)
10
70
75 80
YEARS
85
Figure 17
Projected Changes in Population, Generation, and
Budget for the City of Cleveland
-------
REFERENCES
1. Clark, Robert M., Management Information For Solid
Waste Collection, Environmental Protection Series
EPA-R2-72-012, National Environmental Research
Center, Office of Research and Monitoring, IT. S.
Environmental Protection Agency, Cincinnati,
Ohio 45268.
2. Clark, Robert M., and Helms, Billy P., "Decentralized
Solid Waste Collection Facilities," Journal of the
Sanitary Engineering Division, American Society of
Civil Engineers, Vol. 96, No. SA5, Proc. Paper 7594,
October 1970, Pages 1035-1043.
3. Clark, Robert M., Sweeten, John M., and Greathouse,
Daniel G., "Basic Data For Solid Waste: A Pilot
Study," Journal of the Sanitary Engineering Division,
American Society of Civil Engineers, Vol. 98, No. SAG,
Proc. Paper 9424, December 1972, Pages 897-907.
4. Marks, David H., and Liebman, J. C., Mathematical Analysis
of Solid Waste Collectiqn, Public Health Service Pub-
lication No. 2104, 1970.
5. Marks, David H., ReVelle, Charles S., and Liebman, Jon C.,
"Mathematical Models of Location: A Review,"
Journal of the Urban Planning and Development Division
American Socity of Civil Engineers,Vol.95^No.UP1,
March 1970, Pages 81-93.
6. Quon, Jimmie E., Tanaka, Masaru, and Wersan, Stephen J.,
"Simulation Models of Refuse Collection Policies,"
Journal of the Sanitary Engineering Division, Ameri-
can Society of Civil Engineers,Vol.95,No. SA3,
Proc. Paper 6626, June 1969, Pages 575-592.
7, Truitt, M. M., Liebman, J. C., and Kruse, C. W., "Simula-
tion Model of Urban Refuse Collection," Journal of
the Sanitary Engineering Division, American Society
of Civil Engineers, Vol. 95, No. SA2, April 1969.
36
-------
BiBLIOGRAPHIC DATA
SHEET
1. Kcport No.
EPA-670/5-73-12
3. Recipient's Accession No.
4, Title and Subt itlc
"Systems Simulation and Solid Waste Planning;
A Case Study"
5- Report Date
1973-issuing date
6.
7, Autlior(s)
R. M. Clark and J. I. Gillean
8. Performing Organization Rept.
No.
9. Performing Organization Name and Address
U. S. Environmental Protection Agency
National Environmental Research Center
Office of Research and Development
Cincinnati, Ohio 45268
10. Project/Task/K'ork Unit No.
11. Contract /Grant No.
12. Sponsoring Organization Name and Address
Same as above.
13. Type of Report & Period
Covered
14.
15. Supplementary Notes
16. Abstracts Adequate solid waste management planning is one of the major
problems facing most medium-to-large urban communities in the U. S. In-
creasing waste generation, difficulties in labor-management relations,
decreasing land resources, increasing effluent standards, rising cost,
and uncertain technology are only a few of the problems facing today's
solid waste managers. A technique which is often suggested as a means
of bringing these kinds of problems under control is the so called
"systems approach." This phrase as generally used is often vaguely
defined and is many times totally meaningless. The work cited in this
report is a successful application of systems analysis to solid waste
management problems in Cleveland, Ohio, and is intended to illustrate
the power of the "systems approach" when properly applied. It is hoped
that the work cited in this report will be helpful to other communities
in the solution of their solid waste management problems.
17. Key V.'ords and Document Analysis. 17a. Descriptors
Urban planning, computation, computers, costs, data systems, economic
analysis, management, solid wastes, and systems engineering.
17b. Idcmifiers/Open-Ended Terms
Systems analysis, simulation modeling, and management information systems
17c- C.OSAT! Field/Group
18. Availability Statement
Release to public.
37
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