Document Type : Research Paper


1 Assistant professor, Department of Industrial Engineering, Khatam University, Tehran, Iran

2 Msc. Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran

3 Msc.Industrial Engineering, Department of Industrial Engineering, Khatam University, Tehran, Iran


This paper proposes a bi-objective model for the waste collection problem and considers the location, routing and inventory of the system simultaneously. Considering the reverse flow of the system is another feature of the current study. In the proposed model, the total costs of the system are minimized. In addition, the related risks of opening new centers and transportaion are included as the second objective function of the problem. Considering the delivery time and cpacity of vehicels constraints, are the other features of the model. Due to the NP-hardness of the model, two metaheuristic algorithms namely a non dominated sort ordering genetic algorithm (NSGA-II) and a multi objective particle swarm optimization algorithm (MOPSO) are applied to solve the problem. According to the results, NSGA-II is able to reach better answers in all the propsed metrics. According to sesitivity analysis, foreign transportation fleets make a great impact on the costs of the system.


اعتباری, ترابی, نیلوفر. (2019). ارائه مدل مکانیابی-مسیریابی ظرفیت دار پویا با در نظرگرفتن تقاضای وابسته به قیمت. مطالعات مدیریت صنعتی17(52), 89-124.‎
خانی, خلج, مهران, خلج. (2019). مدلی ریاضی دو هدفه مبتنی بر رویکرد برنامه‌ریزی استوار برای مسألۀ مکان‌یابی–موجودی با در نظرگرفتن قابلیت اطمینان پاسخگویی تقاضا و تخفیفات چند سطحی. مطالعات مدیریت صنعتی16(51), 265-300.‎
نوری هرزویلی, حسینی مطلق, نعمت الهی. (2019). ارائه مدل ریاضی جهت هماهنگی تصمیمات سیستم موجودی مرور دوره ای و تسهیم سود در زنجیره تامین دوسطحی غیرمتمرکز با استفاده از قرارداد تخفیف مقداری. مطالعات مدیریت صنعتی,17(52), 287-338.‎
وحدانی, بهنام, طاهروردی. (2019). ارائه یک مدل برنامه ریزی چند هدفه برای مسئله مکان یابی–موجودی-مسیریابی در یک شبکه زنجیره تامین چند سطحی با در نظر گرفتن حداکثر پوشش تقاضا. مطالعات مدیریت صنعتی17(52), 239-286.‎
Alumur, S., & Kara, B. Y. (2007). A new model for the hazardous waste location-routing problem. Computers & Operations Research34(5), 1406-1423.
Baumgarten, H., Klinkner, R., & Sommer-Dittrich*, T. (2004). Reconfigurable logistics systems in production and disassembly networks. International journal of production research42(17), 3647-3655.
Buhrkal, K., Larsen, A., & Ropke, S. (2012). The waste collection vehicle routing problem with time windows in a city logistics context. Procedia-Social and Behavioral Sciences39, 241-254.
Dekker, R., Fleischmann, M., Inderfurth, K., & van Wassenhove, L. N. (Eds.). (2013). Reverse logistics: quantitative models for closed-loop supply chains. Springer Science & Business Media.
El-Sherbeny, N. A. (2010). Vehicle routing with time windows: An overview of exact, heuristic and metaheuristic methods. Journal of King Saud University-Science22(3), 123-131.
Field, J. M., & Sroufe, R. P. (2007). The use of recycled materials in manufacturing: implications for supply chain management and operations strategy. International Journal of Production Research45(18-19), 4439-4463.
Hiassat, A., Diabat, A., & Rahwan, I. (2017). A genetic algorithm approach for location-inventory-routing problem with perishable products. Journal of manufacturing systems42, 93-103.
Hicks, C., Heidrich, O., McGovern, T., & Donnelly, T. (2004). A functional model of supply chains and waste. International Journal of Production Economics89(2), 165-174.
Javid, A. A., & Azad, N. (2010). Incorporating location, routing and inventory decisions in supply chain network design. Transportation Research Part E: Logistics and Transportation Review46(5), 582-597.
Nakhai Kamalabadi, I. (2016). A new mathematical model for the closed-loop supply chains considering pricing for product, a fleet of heterogeneous vehicles, and inventory costs. Journal of Optimization in Industrial Engineering10(21), 29-40.
Nekooghadirli, N., Tavakkoli-Moghaddam, R., Ghezavati, V. R., & Javanmard, S. H. (2014). Solving a new bi-objective location-routing-inventory problem in a distribution network by meta-heuristics. Computers & Industrial Engineering76, 204-221.
Rabbani, M., Farrokhi-Asl, H., & Asgarian, B. (2017). Solving a bi-objective location routing problem by a NSGA-II combined with clustering approach: application in waste collection problem. Journal of Industrial Engineering International13(1), 13-27.
Rabbani, M., Heidari, R., Farrokhi-Asl, H., & Rahimi, N. (2018). Using metaheuristic algorithms to solve a multi-objective industrial hazardous waste location-routing problem considering incompatible waste types. Journal of Cleaner Production170, 227-241.
Tavakkoli-Moghaddam, R., & Raziei, Z. (2016). A new bi-objective location-routing-inventory problem with fuzzy demands. IFAC-PapersOnLine49(12), 1116-1121.
Validi, S., Bhattacharya, A., & Byrne, P. J. (2015). A solution method for a two-layer sustainable supply chain distribution model. Computers & Operations Research54, 204-217.
Yuchi, Q., He, Z., Yang, Z., & Wang, N. (2016). A location-inventory-routing problem in forward and reverse logistics network design. Discrete Dynamics in Nature and Society2016.
Zhalechian, M., Tavakkoli-Moghaddam, R., Zahiri, B., & Mohammadi, M. (2016). Sustainable design of a closed-loop location-routing-inventory supply chain network under mixed uncertainty. Transportation Research Part E: Logistics and Transportation Review89, 182-214.
Zhang, Y., Qi, M., Lin, W. H., & Miao, L. (2015). A metaheuristic approach to the reliable location routing problem under disruptions. Transportation Research Part E: Logistics and Transportation Review83, 90.