Abstract
One of the major concerns in a reverse supply chain management (RSCM) system is dealing with returned products (due to being defective or obsolete) through a reverse logistics, such that the returned items reach their final destinations with minimum cost. In this paper, for managing returned products, a comprehensive seven-layer recovery network is designed, including primary customers, collection/redistribution centers, recovery, recycling and disposal centers, and secondary customers. The network is mathematically modeled as a mixed integer linear programming (MILP) model whose optimal solution determines the proper collection and recycling centers for the reverse and forward logistics of returned and recovered products, such that the total cost is minimized. Since the problem belongs to the network design class of problems which is NP-hard, the time for obtaining an optimal solution grows exponentially as the number of binary variables increases. Therefore, a new Tabu search-based heuristic method is developed for computing optimal or near-optimal solutions for the recovery system. Also, the Taguchi experimental design technique is employed for parameter tuning of the heuristic and coming up with a robust design. The efficiency and effectiveness of the proposed heuristic method has been evaluated through comparisons with a recently developed SA method, as well as the global optimal solutions of the model. Experimental results showed that the new Tabu search-based approach outperforms the SA method and has an average solution gap of 3.28 % with optimal solutions and a robustness of 2.18 %.
Similar content being viewed by others
References
Pishvaee M, Farahani R, Dullaert W (2010) A memetic algorithm for bi-objective integrated forward/reverse logistics network design. Comput Oper Res 37(6):1100–1112
Ferguson RB (2000) IBM Dell move to reverse logistics. E Week, 17(40):20
Grenchus E, Johnson S, McDonell D (2001) Improving environmental performance through reverse logistics at IBM. In Proceedings of the 2001 IEEE International Symposium on Electronics and the Environment, pp 236–240
Ravi V, Shankar R, Tiwari MK (2005) Analyzing alternatives in reverse logistics for end-of-life computers: ANP and balanced scorecard approach. Comput Ind Eng 48(2):327–356
Bastiaan Janse B, Schuur P, Brito M (2009) A reverse logistics diagnostic tool: the case of the consumer electronics industry. Int J Adv Manuf Technol 47(5–8):495–513
Blumberg D (1999) Strategic examination of reverse logistics and repair service requirements, needs, market size and opportunities. J Bus Logist 20(2):141–159
Du F, Evans G (2008) A bi-objective reverse logistics network analysis for post-sale service. Comput Oper Res 35(8):2617–2634
Meade L, Sarkis J, Presley A (2007) The theory and practice of reverse logistics. Int J Logist Syst Manag 3(1):56–84
Aras N, Aksen D (2008) Locating collection centers for distance and incentive dependent returns. Int J Prod Econ 111(2):316–333
Srivastava SK (2008) Network design for reverse logistics. Omega 36(4):535–548
Wadhwa S, Madaan J, Chan F (2009) Flexible decision modeling of reverse logistics system: a value adding MCDM approach for alternative selection. Robot Comput Integr Manuf 25(2):460–469
Gou Q, Liang L, Huang Z, Xu C (2008) A joint inventory model for an open-loop reverse supply chain. Int J Prod Econ 116(1):28–42
Hui Oh Y, Hwang H (2006) Deterministic inventory model for recycling system. J Intell Manuf 17(4):423–428
Tao Z, Xin T, Jie Z, Xin L (2008) Improved ant colony system for VRPSPD with maximum distance constraint. Syst Eng Theory Pract 28(1):123–140
Kim H, Yang J, Lee K (2009) Vehicle routing in reverse logistics for recycling end-of-life consumer electronic goods in South Korea. Transp Res D 14(5):291–299
Aras N, Aksen D, Tanug˘ur A (2008) Locating collection centers for incentive-dependent returns under a pick-up policy with capacitated vehicles. Eur J Oper Res 191(3):1223–1240
Rivera R, Erte J (2009) Reverse logistics network design for the collection of end-of-life vehicles in Mexico. Eur J Oper Res 196(3):930–939
Lee C, Chan T (2009) Development of RFID-based reverse logistics system. Expert Syst Appl 36(5):9299–9307
Kannana G, Pokharel S, Kumarc P (2009) A hybrid approach using ISM and fuzzy TOPSIS for the selection of reverse logistics provider. Resour Conserv Recycl 54(1):28–36
Ko H, Evans G (2007) A genetic algorithm-based heuristic for the dynamic integrated forward/reverse logistics network for 3PLs. Comput Oper Res 34(2):346–366
Liang Y, Pokharel S, Lim G (2009) Pricing used products for remanufacturing. Eur J Oper Res 193(2):390–395
Tagaras G, Zikopoulos C (2008) Optimal location and value of timely sorting of used items in a remanufacturing supply chain with multiple collection sites. Int J Prod Econ 115(2):424–432
Ostlin J, Sundin E, Bjorkman M (2008) Importance of closed-loop supply chain relationships for product remanufacturing. Int J Prod Econ 115(2):336–348
Biehl M, Prater E, Realff M (2007) Assessing performance and uncertainty in developing carpet. Comput Oper Res 34(2):443–463
Figueiredo J, Mayerle S (2008) Designing minimum-cost recycling collection networks with required throughput. Transp Res E 44(5):731–752
Blanc H, Fleuren H, Krikke H (2004) Redesign of a recycling system for LPG-tanks. OR Spectr 26(2):283–304
Mutha A, Pokharel S (2009) Strategic network design for reverse logistics and remanufacturing using new and old product modules. Comput Ind Eng 56(1):334–346
Yongsheng Z, Shouyang W (2008) Generic model of reverse logistics network design. J Transp Syst Eng Inf Technol 8(3):71–78
Jayaraman V, Patterson R, Rolland E (2003) The design of reverse distribution networks: models and solution procedures. Eur J Oper Res 150(1):128–149
Demirel N, Gökçen H (2008) A mixed integer programming model for remanufacturing in reverse logistics environment. Int J Adv Manuf Technol 39(11–12):1197–1206
Kim K, Song I, Kim J, Jeong B (2006) Supply planning model for remanufacturing system in reverse logistics environment. Comput Ind Eng 51(2):279–287
Lee D, Dong M (2008) A heuristic approach to logistics network design for end of lease computer products recovery. Transp Res E 44(3):455–474
Lee D, Dong M (2009) Dynamic network design for reverse logistics operations under uncertainty. Transp Res E 45(1):61–71
Listes O (2007) A generic stochastic model for supply-and-return network design. Comput Oper Res 34(2):417–442
Lu Z, Bostel N (2007) A facility location model for logistics systems including reverse flows: the case of remanufacturing activities. Comput Oper Res 34(2):299–323
Min H, Ko H (2008) The dynamic design of a reverse logistics network from the perspective of third-party logistics service providers. Int J Prod Econ 113(1):176–192
Pati R, Vrat P, Kumar P (2008) A goal programming model for paper recycling system. Omega 36(3):405–417
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
Pishvaee M, Kianfar K, Karimi B (2009) Reverse logistics network design using simulated annealing. Int J Adv Manuf Technol 47(1–4):269–281
Qin Z, Ji X (2010) Logistics network design for product recovery in fuzzy environment. Eur J Oper Res 202(2):479–490
Salema M, Povoa A, Novais A (2007) An optimization model for the design of a capacitated multi-product reverse logistics network with uncertainty. Eur J Oper Res 179(3):1063–1079
Sayed M, Afia N, Kharbotly A (2008) A stochastic model for forward–reverse logistics network design under risk. Comput Ind Eng 58(3):423–431
Wang H, Hsu H (2010) A closed-loop logistic model with a spanning-tree based genetic algorithm. Comput Oper Res 37(2):376–389
Chopra S (2003) Designing the distribution network in a supply chain. Transp Res Part E Logist Transp Rev 39(2):123–140
Glover F (1989) Tabu search - Part I. ORSA J Comput 1(3):190–206
Glover F (1990) Tabu search - Part II. ORSA J Comput 2(1):4–32
Gen M, Altiparmak F, Lin L (2006) A genetic algorithm for two-stage transportation problem using priority-based encoding. OR Spectr 28(3):337–354
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Eskandarpour, M., Masehian, E., Soltani, R. et al. A reverse logistics network for recovery systems and a robust metaheuristic solution approach. Int J Adv Manuf Technol 74, 1393–1406 (2014). https://doi.org/10.1007/s00170-014-6045-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00170-014-6045-7