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 Pro TM 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:apaydin@yildiz.edu.tr, 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 7 o C. 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 7m 3. 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 Pro TM 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 HIZIRBEY PAZARKAPI (26.1 ha) CARSI (15.6 ha) KEMERKAYA GULBAHARHATUN ORTAHISAR Figure 1. Quarters studied in Trabzon City Pazarkapi Via 50 Finish 1 Via 55 Via 48 Via 45 Via 44 Via 49 Via 46 Via 54 Via 43 Via 53 0 Via 51 Via 39 Via 38 Via 40Via 42 Via 34Via 35 Via 41 Via 37 Via 36 Via 47 Via 33 Via 52 Start Via 1 Via 30Via 29 Via 28 Via 31 Via 27 Via 2 Via 3 Via 26 Via 4 Via 5 Via 9 Via 6 Via 8 Via 7 Carsi Via 25 Via 13 Via 10Via Via 11 12 Via 18 Via 16 Via 17 Via 24 Via 23 Via 20Via 21 Via 22 Via 32 Via 15 Via 19 Via 14 Figure 2. Çarşı Neigbourhood Present Route: 4833m 251
Ö. Apaydın, E. Arslankaya, Y. Avşar, M. T. Gönüllü Sigma 2004/4 Pazarkapi Via 54 1 Via 55 Finish Via 52 Via 39 0 Via 40 Via 38 Via 41 Via 37 Via 42 Via 43 Via 31 Via 44 Via 51 Via Via 36 Via 35 Via 34 Via 33 32 Via 49 Via 48 Via 47 Via 50 Via 46 Via 53 Via 45 Start Via 1 Via 30 Via 29 Via 27 Via 28 Via 2 Via 3 Via 26 Via 4 Via 5 Via 25 Via 24 Via 6 Via 7 Carsi Via 17 Via 15 Via 8 Via 23 Via 16 Via 22 Via 21 Via 18Via 19 Via 20 Via 10 Via 13Via 12 Via 11 Via 14 Via 9 Figure 3. Çarşı Neigbourhood Optimized Route: 3867m Table 1. Analysis of turn numbers and time spends Present Route Optimized Route Number Total Turn Time (s) Number Total Turn Time (s) Right turn 32 303 17 162 Left turn 26 240 25 228 Total 58 543 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... Frequency 25 20 15 10 5 0 21 65% 14 39% 80% 8 89% 5 93% 2 96% 98% 2 1 1 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 0-45 45-90 90-135 135-180 180-225 225-270 270-315 315-360 Distance, m Figure 4. Intervals between container distances on present route Frequency 25 20 15 10 5 0 22 70% 16 40% 85% 8 96% 6 98% 1 1 0 0 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 0-45 45-90 90-135 135-180 180-225 225-270 270-315 315-360 Distance, m Figure 5. Histogram intervals between container distances for optimized route 253
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] Sonesson U., Modelling waste collection-a general approach to calculate fuel consumption and time, Waste Management&Research, 18, 115-123, 2000. [2] 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. [3] Keles R., The Management of the coastal zone of Trabzon City, Trabzon, 1995. [4] 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. 254