249 GIS SUPPORTED OPTIMIZATION OF SOLID WASTE

Journal of Engineering and Natural Sciences
Mühendislik ve Fen Bilimleri Dergisi
Sigma
2004/4
GIS SUPPORTED OPTIMIZATION OF SOLID WASTE COLLECTION IN
TRABZON
Ömer APAYDIN*, Ertan ARSLANKAYA, Yaşar AVŞAR, M. Talha GÖNÜLLÜ
Yıldız Teknik Üniversitesi , İnşaat Fakültesi, Çevre Mühendisliği Bölümü, Yıldız-İSTANBUL
Geliş/Received: 14.06.2004 Kabul/Accepted: 04.11.2004
ABSTRACT
In the municipal solid waste management systems, collection and hauling efforts cover 85 percent of total
system expenditures that make quite huge amount of money for societies. In order to get reduction on those
and to save resources, searching for optimization possibilities gains importance. In case of not using an
optimization on collection, total cost of the disposal management of the solid waste is getting increased
because of “empty mile negativeness. In this study, to minimize the route and collection cost was objected.
For that purpose, as an optimization tool, RouteView ProTM software was used. Comparison with present
collection routes and optimized routes was pointed out a success as average 20% percent route length in
decrease of entire collection job. The numbers of turns on the route and time spends also can be decreased as
30%.
Keywords: Solid waste collection, route optimization, turns, GIS, Trabzon.
TRABZON’DA KATI ATIK TOPLAMA İŞLEMİNİN CBS DESTEKLİ OPTİMİZASYONU
ÖZET
Katı atık bertaraf işlemlerinde toplama/taşıma maliyetleri toplam maliyetin %85’lik kısmını teşkil eder. Bu
maliyetin azaltılması ve kaynak koruma amacıyla optimizasyon işlemlerinin araştırılması önem arz
etmektedir. Toplama işlemlerinin optimize edilmemesi durumunda “boşa kat edilen yollar” yüzünden katı atık
toplam bertaraf maliyetleri artmaktadır. Yapılan çalışmada en kısa güzergahın belirlemesinde Route View Pro
programı kullanılmıştır. Mevcut güzergah ile optimize edilen güzergah kıyaslandığında aracın kat edeceği yol
%20 oranında azalmaktadır. Katı atık toplama aracının sağa/sola dönüş sayısı da %30 oranında azalmaktadır.
Anahtar Sözcükler: Katı atık toplama, güzergah optimizasyonu, dönüşler, CBS, Trabzon.
1. INTRODUCTION
In the optimization of a solid waste management system, collection and hauling facilities that
constitute for the most part of total disposal payment should be taken into consideration
previously.
In literature, there are several models dealing with collection of waste in broad sense.
One group of the models has an operational research approach, and they minimize costs or total
driving distance by using different numerical methods [1].
*
Sorumlu Yazar/Corresponding Autor: e-mail:[email protected], Tel: (0212) 259 70 70/2968
249
Ö. Apaydın, E. Arslankaya, Y. Avşar, M. T. Gönüllü
Sigma 2004/4
Turkey takes place in the group of medium income level economically. Kinaci et al. [2]
emphasize that yearly collection expenses will be able to drop about 50% when it is used an
optimization research for Istanbul.
In the research, the optimization of present truck routes being used for collection of
solid wastes in Trabzon City is objected.
Trabzon City is located at the North East Part of Turkey and has a typical
Mediterranean climate features. Temperature range is from 26 to –7oC. Daylight hours change
from 16 hours in the summer and 12 hours in the winter. The city covers an area of 40 sq km as
rounded [3]. About 57,000 households have been settled down in the area. There are 39
neighborhoods in the city.
The municipality serves with about 2,800 garbage collecting containers in different
sizes (150, 300, and 400 L) in the residential area. Domestic wastes from households are dropped
by inhabitants into these containers. Containers are unloaded at least twice a week by about 20
trucks (in total capacity of 154 cu m). On the other hand, waste collection through some busy
streets such as Maraş Caddesi is realized 7-8 times in a day. Total daily tour number in the city
reaches by 50. Collection facility is subjected for 6 days in a week.
Due to the reasons such as not being smooth topographical situation and small city size,
there is not any transfer station in the city yet. Collected garbage is dumped at sea side of Black
Sea by blending with soil in a ratio of about 50%. The dumping area in 2 Ha and has been
prepared as surrounded by breakwater walls on the sea. This kind of dumping creates
considerable sea pollution. In order to reduce the amount of wastes to be landfilled, any recycling
program in charge has not been applied yet [4].
2. AN OPTIMIZATION STUDY OF WASTE COLLECTION
As a beginning study for optimization of existing routes in Trabzon City, Pazarkapı-Çarşı quarters
occupying 1.5% of total area were selected as a pilot area. About 5,000 inhabitants are sited in
this area shown at the map in Figure 1. Selected area for optimization study is historical part and
located at inner side of the city. Selected collection route in the area is employed by a truck in
7m3.
At the beginning of the study, first, a geo coded road map was produced. Following that
work, sub-layers composing of population density and waste amount distribution were created.
By this stochastic study, minimization of total route distance and so, collection cost was objected.
For that purpose, RouteView ProTM being in the basis of dynamic programming and giving visual
results was operated.
Present route to be optimized has been shown in Figure 2. The truck starts from
Pazarkapı quarter and ends Çarşı quarter. After taking last MSW container in Çarşı quarter, the
truck transports compacted contents to available landfill site. Total travel distance of present route
is 4833m.
Optimized distance was 3867 m as may be observed from Figure 3. Optimization
facility occupied for shortest distance was supplied a benefit of 20%. The study has been supplied
a visual correction possibility on present collection route. This type of optimization trials helps to
local waste managers by gaining fault correction skill.
3. RESULTS
To analysis of this visual optimization output, right and left turn numbers and distances between
following containers were evaluated.
Table 1 contains of right/left turn numbers for present/optimized routes and time spends
during turns. Particularly, in the right turn numbers, a substantial decrease is observed (about
50%). Depending on this state, time spends are also get decreased. On the contrary to this, only a
250
GIS Supported Optimization of Solid Waste...
few benefit for left turns is contributed. Total benefit for the entire turns reaches up to roughly
30%.
MSW DISPOSAL AREA (2 ha)
BLACK SEA
BLACK SEA
PAZARKAPI
(26.1 ha)
HIZIRBEY
CARSI
KEMERKAYA
(15.6 ha)
GULBAHARHATUN
ORTAHISAR
Figure 1. Quarters studied in Trabzon City
Pazarkapi
Start Via 1
Finish
1
Via 49
Β
Β
Β
Β
Β
Β
Β Via 43
Β
Via 53
Β
Β
Via 52
Β
Β
Β 51
Via
Via 29
Via 28
Via 30
Β Β Β
Via 39
ΒVia 38 Via 40 Via 42
Via 34Via 35Β Β Β Β Β
Via 41
Β Β Β Via 37
Via 36
Β
Β 33
Via
Via 26
Via 27
Via 24
Β
ΒVia 3
Β
Β
Via 31
Β
Via 25
Via 2
Via 44
Via 46
Via 54
Via 47
Via 50
0
Via 55Via 48 Via 45
Β
Via 9
Β
Via 4
Β
Via 13
Via 10
Via Via
11 12
Β Β Β Β
Via 8
Β
Β
Carsi
Via 5
Via 17
Β
Via 6
Β
Via 32
Via 7
Β
Via 15
Β
Β
Figure 2. Çarşı Neigbourhood Present Route: 4833m
251
Via 23
ΒVia 18
Β
Via 16 ΒVia 20
Via 21 Via 22
Β
Β Β Β
Via 19
Β
Via 14
Β
Ö. Apaydın, E. Arslankaya, Y. Avşar, M. T. Gönüllü
Sigma 2004/4
Pazarkapi
Start Via 1
Finish
1
Via 55
Β
Via 53Via 52 Via 39
Β Β
Β 40 Via 38
Via
Β
Via Β
41
Β 42
Via
Via 37
Β
Β 43
Via
Via 54
Β
0Β
Via 31
Β
Β
Via 44
Β Via 28
Β
Via
34
Via
35
Via
Via
33
32
Via 36
Β
Β
Via 48Β Β Β Β Β
Via 49
Via 47
Β Β Via
Β 46
Via 50
Β
Β
Via 22
Β
ΒVia 3
Via 29
Via 27 Β
Via 30
Β Β Β
Via 26
Via 51
Via 23
Via 2
Β
Via 25
Β
Via 4
Via 21
Via 18
Via 19
Via 20
Β Β ΒΒ
Via 24
Β
Β
Carsi
Via 5
Via 16
ΒVia 17
Β
Via 6
Β
Via 45
Via 7
Β
Β
Β
Via 15 Via 13
Via 12Via 11
Β
Β Β Β
Via 8
Β
Via 10
Β
Via 14
Β
Via 9
Β
Figure 3. Çarşı Neigbourhood Optimized Route: 3867m
Table 1. Analysis of turn numbers and time spends
Right turn
Left turn
Total
Present Route
Number
Total Turn Time (s)
32
303
26
240
58
543
Optimized Route
Number
Total Turn Time (s)
17
162
25
228
42
380
As indicated from Figure 4 and Figure 5 that those state frequencies of distances
between each following containers on present and optimized routes, respectively. Optimization
effort causes shortenings on distances between each following containers. While 65% containers
on the present route have had lower than 90m distance to following containers, 70% containers on
the optimized route have had. Furthermore, distances between following containers on the
optimized route are not more than 270m.
252
GIS Supported Optimization of Solid Waste...
25
89%
21
Frequency
20
96% 98%
93%
80%
65%
14
15
10
39%
8
1
1
315-360
225-270
2
180-225
135-180
90-135
45-90
0-45
0
2
270-315
5
5
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Distance, m
Figure 4. Intervals between container distances on present route
25
22
20
85%
70%
16
15
40%
10
8
6
225-270
0
0
315-360
1
270-315
1
180-225
135-180
90-135
0
45-90
5
0-45
Frequency
98%
96%
Distance, m
Figure 5. Histogram intervals between container distances for optimized route
253
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Ö. Apaydın, E. Arslankaya, Y. Avşar, M. T. Gönüllü
Sigma 2004/4
4. CONCLUSION
This preliminary study made for a limited area to optimize Waste Collection facility in Trabzon
City put forward that optimization conducted for shortest collection route provides 20% benefit
from total distance.
The numbers of turns on the route and time spends also can be decreased as 30%.
Travel distances between each following containers decrease, i.e. they close to each other.
Unit collecting cost in Trabzon city was determined as 0,05$/km*ton. It is determined
that the longer road traveled the more expensive cost on collecting/hauling system. When it is
used the optimized route, approximately 200,000$/year economy will be obtained in Trabzon city
where 150ton/day solid waste is collected. Another gain of the optimized route is vehicle is being
less time in traffic.
Turning of right, and left of vehicle causes decreasing average speed of the vehicle, so
wasting time at route is getting increased. By the optimization route, number of the right turning
undesirable in collecting process will decrease and vehicle speed increase.
ACKNOWLEDGEMENTS
This research has been supported by Yıldız Technical University Scientific Projects Coordination
Department. Project Number : 24/05/02.02.
REFERENCES
[1]
[2]
[3]
[4]
Sonesson U., “Modelling waste collection-a general approach to calculate fuel
consumption and time”, Waste Management&Research, 18, 115-123, 2000.
Kinaci C., Gorgun E., Arslan M., Armagan B., “Private Sector Participation in Municipal
Solid Waste Services-A Case Study for Kadıkoy of Istanbul in Turkey”, Wastecon 2000,
Biennial Conferance and Exhibition on Integrated Waste Management in The
Millennium, Cape Town, South Africa, September, 2000.
Keles R., The Management of the coastal zone of Trabzon City, Trabzon, 1995.
Apaydin O., Kalender A., Gonullu M.T., “Assessment of Sociological Aspect of Separate
Household Solid Waste Collection in Trabzon (Turkey)”, ISWA 2002 World
Environmental Congress.
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