پديد آورندگان :
باقري، كيوان دانشگاه تهران - دانشكده جغرافيا - سنجش ازدور , نيساني ساماني، نجمه دانشگاه تهران - دانشكده جغرافيا , جلوخاني نياركي، محمدرضا دانشگاه تهران - دانشكده جغرافيا
چكيده فارسي :
موضوع جمع آوري پسماند يك چالش بزرگ براي جوامع مدرن ميباشد حدود 80% از كل هزينه مديريت پسماند را شامل ميشود. بنابراين برنامه‌ريزي صحيح جمع‌آوري پسماند جهت به‌كارگيري اصولي منابع، مي‌تواند از ايجاد هزينه‌هاي اضافي جلوگيري نمايد و موجب بالا رفتن اثربخشي و درنهايت بهره‌وري مديريت پسماند گردد. هدف از اين تحقيق، يافتن مسيريهاي مناسب جمع آوري پسماند شهري با استفاده از دادههاي مكان مبنا طوريكه زمان مجموع سفرهاي وسايل نقليه كمينه كردن شود. از طرفي محدوديتهاي حداكثر زمان مسافرت، حداكثر كل فاصله ي طي شده، حداكثر تعداد سطل زباله بررسي شده رعايت شود. در اين تحقيق از تلفيق مسئله مسيريابي وسيله نقليه (VRP) با سيستم اطلاعات جغرافيايي (GIS) استفاده ميشود. سناريوهاي تحقيق بر پايه يك ناوگان ثابت غيريكنواخت با تعداد ثابتي از هر نوع ماشين با هزينه و ظرفيت‌هاي محدود و متفاوت ميباشد. مسئله سازگار شده تحقيق با توجه به ويژگيهاي جمع آوري پسماند، مسئله مسيريابي وسايل نقليه با ظرفيت دار نا متقارن و پنجره زماني نرم[1] (ACVRPTWS) ميباشد. در ادامه به منظور اجراي يك نمونه كاربردي از مسئله مورد نظر برروي مسئله جمع‌آوري پسماند در يك پايلوت از شهر تهران موردبررسي قرار گرفت. در ادامه نتايج حاصل از ACVRPTWS با واقعيت مقايسه شده و نشان از كاهش 14 و 24 درصدي زمان مسافرت و زمان كل مسافرت ميدهد. در واقع با استفاده از اين روش مي توان شبكهاي طراحي كرد كه به كمك آن كاهش قابل توجهي در هزينه هاي جمع آوري پسماند داشته باشد به عبارت ديگر الگوريتم پيشنهادي توانسته است يك تناسب منطقي بين تعداد سطل هاي زباله مورد بررسي، حجم پسماند جمع آوري شده، مسافت پيموده شده و مدت زمان سرويس دهي هر وسليه نقليه برقرار كند . لازم به ذكر است كه الگوريتم پيشنهادي در 5 دقيقه اجرا شده است.
چكيده لاتين :
Municipal solid waste collection is expensive and, in some cities, 46–85% of their whole waste management expenses are used for waste collection and transportation. Rapid urbanization and every day human actions generate a large amount of waste from residential, commercial, or industrial extents all over the world. Waste collection optimization can decrease the waste collection budget and environmental emissions by reducing the collection route distance. Therefore, suitable planning of waste collection process can prevent additional costs and increase the efficiency of waste management. This paper aims to find appropriate routes for municipal waste collection using geospatial data to minimize total travel time of vehicles. On the other hand, the constraint set for the maximum travel time, the maximum total distance traveled, and the maximum number of checked waste bins have to be taken into account. In this research, the integration of the Vehicle Routing Problem (VRP) with the Geographic Information System (GIS) is used. Research scenarios are considered based on a fixed non-uniform fleet with a constant number of each types of vehicles in the Asymmetric Capacitated Vehicle Routing Problem with Backhauls and with Time Windows (ACVRPTW). The reason for choosing the ACVRPTW for this research is that in urban traffic network, vehicles have limited capacity, also urban passages are oriented asymmetrically, on the other hand, the time of service to buckets garbage is important and they should be viewed in a time window.
In order to implement the proposed method, first, location data of waste bins and the average amount of waste generated per day are prepared. Also, the standards and policies of the waste management organization including the number and types of vehicles with their characteristics such as capacity and fuel consumption should be provided. The amount of waste generated by each trash should be calculated further. These data provide a pattern for the amount of waste accumulated in each garbage bin. The next step is solving the routing problem; in fact, the same VRP is executed in a specific way with the restrictions, parameters, and target function of the ACVRPTW. Then, the evaluation of the results will be accomplished.
ACVRPTW was surveyed in a case study of Tehran, Iran. The results of the ACVRPTW are compared with real applications, indicating a decrease of 14% and 24% in each trip and whole travel time. In addition, the results also indicate that this research clearly contains a scientific approach to urban waste collection systems, and the proposed algorithm is able to take into account the constraints that the waste management organization has put forward. Furthermore, it determined the optimal time routes for each vehicle according to its characteristics. In fact, with this method, a network can be designed in order to reduce waste collection costs significantly. In other words, the proposed algorithm has been able to find an appropriate balance between the numbers of examined waste bins, the amount of collected waste, the mileage, and the duration time that each vehicle is serviced. It should be noted that the proposed algorithm runs in 5 minutes on average
