A Robust Multi-objective Model for Designing Reverse Supply Chain Network via Considering Dynamic Pricing under Uncertainty and a Parallel Memetic Solution Algorithm

Document Type : Research Paper

Authors

1 University of shahrood

2 University of Shahrood

Abstract

Design of reverse supply chain network (RSCN) to efficiently manage the flow of returned products is one of the most important issues in supply chain management. Determining an acquisition price of returned products which could be affected by different factors such as product quality levels has a significant effect on strategic design of RSCN. In this paper, a comprehensive mathematical model for designing a multi-level RSCN with a dynamic pricing approach for returned products which is affected by product quality levels. In order to manage the uncertainty of number of returned products, a robust optimization based on the uncertainty budget approach is considered. The aim of the proposed model is to design the RSCN to maximize the RSCN total profit and responding to customer demands simultaneously. Due to the NP-hard nature of the network design problems, a memetic algorithm based on the non-dominated sorting genetic algorithm II and parallel adaptive variable neighborhood search is proposed to find the optimal Pareto solutions. The performance of the proposed memetic algorithm is compared with multiple similar algorithms. The computational results indicate a significant impact of the dynamic pricing approach on the performance of the reverse logistic network. In addition, using the robust optimization based on the uncertainty budget approach can efficiently handle various conservatism levels of decision makers under uncertainty of the business environment. Finally, the obtained results show the significant superiority of the proposed hybrid meta-heuristic algorithm to solve a multi-objective RSCN design model via considering the dynamic pricing approach under uncertainty.

Keywords

Main Subjects


[1]     Ilgin, M., Gupta, S., (2010), "Environmentally Conscious Manufacturing and Product Recovery: A Review of The State of The Art", Journal of Environmental Management 91(3): 563–591.
[2]     Govindan, K., Soleimani, H., D. Kannan. D., (2015), "Reverse Logistics and Closed-Loop Supply Chain: A Comprehensive Review To Explore The Future", European Journal of Operational Research 240: 603–626.
[3]     Niknejad, A., Petrovic., D., (2014), "Optimization of Integrated Reverse Logistics Networks With Different Product Recovery Routes", European Journal of Operational Research 238:143–154.
[4]     Meepetchdee, Y., Shah. N., (2007), "Logistical Network Design With Robustness And Complexity Considerations", Int. J. Phys. Distrib. Logist. Manag 37(3): 201–222.
[5]     Eskandarpour, M., Masehian, E., Soltani, R., Khosrojerdi, A., (2014), "A Reverse Logistics Network For Recovery Systems and A Robust Metaheuristic Solution Approach", Int J Adv Manuf Technol 74: 1393–1406.
[6]     Aras, N., Aksen, D., Tanugur. A.G., (2008), "Locating Collection Centers For Incentive-Dependent Returns Under A Pick-Up Policy With Capacitated Vehicles", European Journal of Operational Research 3: 223-1240.
[7]     Keyvanshokooh, E., Seyed-Hosseini, S.M.,  Tavakkoli-Moghaddam, R., (2013), "Dynamic Pricing Approach For Returned Products In Integrated Forward/Reverse Logistics Network Design", Applied Mathematical Modelling 37: 10182-10202.
[8]     Liang, Y., Pokharel., S, Lim., G., (2009), "Pricing Used Products For Remanufacturing", Eur J Oper Res. 193(2): 390–395.
[9]     Pokharel, S., Mutha., A., (2009), "Perspectives In Reverse Logistics: A Review". Resour. Conserv. Recycl. 53: 175–182.
[10] Altiparmak, F., Gen, M., Lin, L., Karaoglan, I., (2008), "A Steady-State Genetic Algorithm For Multi-Product Supply Chain Network Design", Computers & Industrial Engineering 56: 521-537.
[11] Roghanian, E., Pazhoheshfar. P., (2014), "An Optimization Model For Reverse Logistics Network Under Stochastic Environment By Using Genetic Algorithm", Journal of Manufacturing Systems 33: 348–356.
[12] Kannan, G., Sasikumar, P., Devika., K., (2010), "A Genetic Algorithm Approach For Solving A Closed Loop Supply Chain Model: A Case Of Battery Recycling", Appl. Math. Modell 34: 655–670.
[13] Barros, A.I., Dekker, R., Scholten. V., (1998), "A Two-Level Network For Recycling Sand: A Case Study", Eur. J. Oper. Res 110 (2): 199–214.
[14] Louwers, D., Kip, B. J., Peters, E., Souren, F.,Flapper . S. D. P., (1999), "A Facility Location Allocation Model For Reusing Carpet Materials", Comput. Ind. Eng 36(4): 855–869.
[15] Realff, M.J., Ammons, J.C., Newton, D.J., (2004), "Robust Reverse Production System Design For Carpet Recycling", IIE Trans 36 (8): 767–776.
[16] Kara, S.S., Onut,. S., (2010), "A Two-Stage Stochastic And Robust Programming Approach To Strategic Planning of A Reverse Supply Network: The Case Of Paper Recycling", Expert Syst. Appl 37(9): 6129–6137.
[17] Vahdani, B., Tavakkoli-Moghaddam., R. Jolai, F., (2013), "Reliable Design Of A Logistics Network Under Uncertainty: A Fuzzy Possibilistic-Queuing Model", Appl. Math. Modell 37 (5): 3254–3268.
[18] Hasani, A., Zegordi, S.H., Nikbakhsh, E., (2012), "Robust Closed-Loop Supply Chain Network Design For Perishable Goods in Agile Manufacturing Under Uncertainty", International Journal of Production Economics 50(16): 4649-4669.
[19] Hasani, A., Zegordi, S. H., Nikbakhsh, E., (2015), "Robust Closed-Loop Global Supply Chain Network Design Under Uncertainty: The Case of The Medical Device Industry", International Journal of Production Research 53(5): 1596-1624.
[20] Eskandarpour, M., Nikbakhsh, E., Zegordi, S. H., (2014), "Variable Neighborhood Search For The Bi-Objective Post-Sales Network Design Problem: A Fitness Landscape Analysis Approach", Computers & Operations Research 52: 300-314.
[21] Jayaraman, V., Guide, V.D.R., Srivastava, R., (1999), "A closed-loop logistics model for remanufacturing", J. Oper. Res. Soc. 50(5): 497–508.
[22] Krikke, H.R., Harten, A. Schuur, P. C., (1999), Business case Océ: reverse logistic network re-design for copiers", OR Spectr. 21(3): 381–409.
[23] Eskandarpour, M., Zegordi, S.H., Nikbakhsh, E., (2013), "A parallel multi-objective variable neighborhood search for the sustainable post-sales network design", International Journal of Production Economics 145(1): 117-131.
[24]  زارعیان جهرمی، ح.، فلاح نژاد، م. ص. صادقیه، ا.، احمدی یزدی. ه. (1393). مدل بهینه‌سازی چند هدفه استوار در طراحی زنجیره تأمین حلقه بسته پایدار. نشریه پژوهش‌های مهندسی صنایع در سیستم‌های تولید 3: 93-111.
[25] Klausner, M. Hendrickson, C. T., (2000), "Reverse Logistics Strategy For Product Take-Back", Interfaces 3: 156–165.
[26] Aras, N., D. Aksen, D., (2008), Locating Collection Centers For Distance And Incentive Dependent Returns", Int J Prod Econ 111(2): 316–333.
[27] Guide, V.D.R., Teunter, R., Wassenhove, L. N., (2003), "Matching Demand And Supply To Maximize Profits From Remanufacturing", Manufacturing and Service Operations Management 5: 303–316.
[28] Kulshreshtha, P., Sarangi, S., (2001), "No Return, No Refund: Analysis Of Deposit-Refund Systems", Journal of Economic Behavior and Organization 4: 379–394.
[29] Wang, H.F., Hsu, W. H., (2010), "A Closed-Loop Logistic Model With A Spanning-Tree Based Genetic Algorithm", Computers & Operations Research 37(2): 376-389.
[30] Lee, J.E., Gen, M., Rhee, K. G., (2009), "Network  Model  and  Optimization  of  Reverse Logistics  By  Hybrid  Genetic  Algorithm", Comput  Ind  Eng 56: 951–64.
[31] Du, F., Evans, G. W., (2008), "A  Bi-Objective  Reverse  Logistics  Network  Analysis  For  Post-Sale  Service", Comput  Oper  Res 35: 2617–34.
[32] Min, H., Ko, H.J., Ko, C.S., (2006), "A  Genetic  Algorithm  Approach  To  Developing  The  Multiechelon  Reverse  Logistics  Network  For  Product  Returns", Omega 34: 56–69.
[33] Pishvaeea, M.S., Zanjirani Farahani, R. Dullaert, W., (2010), "A Memetic Algorithm for Bi-Objective Integrated Forward/Reverse Logistics Network Design", Computers & Operations Research 37:1100–1112.
[34] Pishvaee, M. Torabi, S., (2010), "A Possibilistic Programming Approach For Closed-Loop Supply Chain Network Design Under Uncertainty", Fuzzy Sets Syst 161(20): 2668-2683.
[35] Bertsimas, D., M. Sim, M., (2004), "The price of robustness", Operations Research 52(1): 35-53.
[36] Fahimnia, B., Farahani, R.Z., Sarkis, J., (2013), "Integrated Aggregate Supply Chain Planning Using Memetic Algorithm–A Performance Analysis Case Study", International Journal of Production Research 15(18):  5354-5373.
[37] Moscato, P., Norman, M.G., (1992), "A Memetic Approach For The Traveling Salesman Problem Implementation of A Computational Ecology For Combinatorial Optimization On Message-Passing Systems", Parallel Computing and Transputer Applications: 177–186.
[38] Altiparmak, F., Gen, M., Lin, L., Paskoy, T., (2006), "A Genetic Algorithm Approach For Multi-Objective Optimization of Supply Chain Networks", Computers & Industrial Engineering 51: 196-215.
[39] Freund, J.E., (2003), "Mathematical Statistics with Application"s. 7th ed. 2003, London, UK: Pearson.