Closed loop supply chain networks: Designs for energy and time value efficiency

International Journal of Production Economics

Volumn 183, Issue , 2017, Pages 382-393

  Kadambala, Dinesh K ^a   Subramanian, Nachiappan ^b   Tiwari, Manoj K ^a   Abdulrahman, Muhammad ^b   Liu, Chang ^c  

^a INDIAN INSTITUTE OF TECHNOLOGY   (India)

^b University of Nottingham   (China)

^c UNIVERSITY OF NOTTINGHAM NINGBO CHINA   (China)

Author keywords

Closed loop supply chain; Multi objective particle swarm optimization; Product recovery; Time sensitive product returns

Indexed keywords

COMPUTER SYSTEM RECOVERY; DECISION MAKING; ECONOMIC AND SOCIAL EFFECTS; ENERGY EFFICIENCY; ENERGY UTILIZATION; GENETIC ALGORITHMS; INTEGER PROGRAMMING; INVESTMENTS; PARTICLE SWARM OPTIMIZATION (PSO); RECYCLING; SENSITIVITY ANALYSIS; SUPPLY CHAINS;

CLOSED-LOOP SUPPLY CHAIN; CLOSED-LOOP SUPPLY CHAIN NETWORKS; CLOSED-LOOP SUPPLY CHAINS (CLSC); INSUFFICIENT INVESTMENTS; MIXED INTEGER LINEAR PROGRAMMING; MULTI OBJECTIVE PARTICLE SWARM OPTIMIZATION; PRODUCT RECOVERY; PRODUCT RETURNS;

MULTIOBJECTIVE OPTIMIZATION;

EID: 84973131343     PISSN: 09255273     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ijpe.2016.02.004     Document Type: Article

References (62)

1. Alvarez-Benitez, J.E., Everson, R.M., Fieldsend, J.E., A MOPSO Algorithm based Exclusively on Pareto Dominance Concepts, 2005, Springer, Berlin, Heidelberg, 459–473.
2. Aras, N., Boyaci, T., Verter, V., Designing the reverse logistics network. Ferguson, M., Souza, G., (eds.) Closed Loop Supply Chains: New Developments to Improve the Sustainability of Business Practices, 2010, CRC Press, Boca Raton, FL 33487-2742, 67–98.
3. Bachlaus, M., Shukla, N., Tiwari, M.K., Shankar, R., Optimization of system reliability using chaos-embedded self-organizing hierarchical particle swarm optimization. Proc. Inst. Mech. Eng. Part O: J. Risk Reliab. 220:2 (2006), 77–91.
4. Beamon, B.M., Sustainability and the future of supply chain management. Oper. Supply Chain Manag. 1:1 (2008), 4–18.
5. Blackburn, J., Guide, V., Souza, G., Van Wassenhove, L.N., Reverse supply chains for commercial returns. Calif. Manag. Rev. 46:2 (2004), 6–22.
6. Carter, C.R., Ellram, L.M., Reverse logistics – a review of the literature and framework for future investigation. J. Bus. Logist. 19:1 (1998), 85–102.
7. Chaabane, A., Ramudhin, A., Paquet, M., Design of sustainable supply chains under the emission trading scheme. Int. J. Prod. Econ. 135:1 (2012), 37–49.
8. Chakraborty, P., Das, S., Roy, G.G., Abraham, A., On convergence of the multi-objective particle swarm optimizers. Inf. Sci. 181:8 (2011), 1411–1425.
9. Choudhary, A., Sarkar, S., Settur, S., Tiwari, M.K., A carbon market sensitive optimization model for integrated forward–reverse logistics. Int. J. Prod. Econ. 164 (2015), 433–444, 10.1016/j.ijpe.2014.08.015.
10. Das, K., Rao Posinasetti, N., Addressing environmental concerns in closed loop supply chain design and planning. Int. J.Prod. Econ. 163:1 (2015), 34–47.
11. Deb, K., Pratap, A., Agarwal, S., Meyarivan, T., A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans. Evol. Comput. 6 (2002), 182–197, 10.1109/4235.996017.
12. Dowlatshahi, S., A strategic framework for the design and implementation of remanufacturing operations in reverse logistics. Int. J. Prod. Res. 43:16 (2005), 3455–3480.
13. Duan, Y., Harley, R.G., Habetler, T.G., 2009. Comparison of Particle Swarm Optimization and Genetic Algorithm in the design of permanent magnet motors. In: Proceedings of the 2009 IEEE 6th International Power Electronics and Motion Control Conference. IEEE. pp. 822–825.
14. Easwaran, G., Üster, H., A closed-loop supply chain network design problem with integrated forward and reverse channel decisions. IIE Trans. 42:11 (2010), 779–792.
15. Eberhart, R., 2002. Multiobjective optimization using dynamic neighborhood particle swarm optimization. In: Proceedings of the 2002 Congress on Evolutionary Computation. CEC’02 (Cat. No.02TH8600). IEEE 2. pp. 1677–1681.
16. El-Sayed, M., Afia, N., El-Kharbotly, A., A stochastic model for forward–reverse logistics network design under risk. Comput. Ind. Eng. 58:3 (2010), 423–431.
17. Fahimnia, B., Sarkis, J., Choudhary, A., Eshragh, A., Tactical supply chain planning under a carbon tax policy scheme: A case study. Int. J. Prod. Econ. 164 (2014), 206–215, 10.1016/j.ijpe.2014.12.015.
18. Ferguson, M.E., Fleischmann, M., Souza, G.C., A profit-maximizing approach to disposition decisions for product returns. Decis. Sci. 42:3 (2011), 773–798.
19. Fieldsend J.E., Singh S., 2002. A multi-objective algorithm based upon particle swarm optimization, an efficient data structure and turbulence. In: Proceedings of U.K. Workshop on Computational Intelligence (UKCI’02). United Kingdom. pp. 37–44.
20. Fleischmann, M., Beullens, P., Bloemhof-Ruwaard, J.M., Wassenhove, L.N., The impact of product recovery on logistics network design. Prod. Oper. Manag. 10:2 (2009), 156–173.
21. Fleischmann, M., Krikke, H.R., Dekker, R., Flapper, S.D.P., A characterisation of logistics networks for product recovery. Omega 28:6 (2000), 653–666.
22. French, M.L., LaForge, R.L., Closed-loop supply chains in process industries: An empirical study of producer re-use issues. J. Oper. Manag. 24:3 (2006), 271–286.
23. Geng, Y., Sarkis, J., Ulgiati, S., Zhang, P., Environment and development. Measuring China׳s circular economy. Science 339:6127 (2013), 1526–1527.
24. Govindan, K., Soleimani, H., Kannan, D., Reverse logistics and closed-loop supply chain: a comprehensive review to explore the future. Eur. J. Oper. Res. 240:3 (2014), 603–626.
25. Govindan, K., Jafarian, A., Khodaverdi, R., Devika, K., Two-echelon multiple-vehicle location–routing problem with time windows for optimization of sustainable supply chain network of perishable food. Int. J. Prod. Econ. 152 (2014), 9–28.
26. Guide, V.D.R. Jr., Muyldermans, L., Van Wassenhove, L.N., Hewlett-packard company unlocks the value potential from time sensitive returns. Interfaces 35:4 (2005), 281–293.
27. Guide, V.D.R., Souza, G.C., Van Wassenhove, L.N., Blackburn, J.D., Time value of commercial product returns. Manag. Sci. 52:8 (2006), 1200–1214.
28. Guide, V.D.R., Van Wassenhove, L.N., The evolution of closed-loop supply chain. Res. Oper. Res. 57:1 (2009), 10–18.
29. Gutowski, T.G., Sahni, S., Boustani, A., Graves, S.C., Remanufacturing and energy savings. Environ. Sci. Technol. 45:10 (2011), 4540–4547.
30. Kennedy, J., Eberhart, R.C., Particle swarm optimization. Proc. IEEE Int. Conf. Neural Netw. 4 (1995), 1942–1948.
31. Ko, H.J., Evans, G.W., A genetic algorithm-based heuristic for the dynamic integrated forward/reverse logistics network for 3PLs. Comput. Oper. Res. 34:2 (2007), 346–366.
32. Krikke, H., Impact of closed-loop network configurations on carbon footprints: A case study in copiers. Resour. Conserv. Recycl. 55:12 (2011), 1196–1205.
33. Krikke, H., Bloemhof-Ruwaard, J., Van Wassenhove, L.N., Concurrent product and closed-loop supply chain design with an application to refrigerators. Int. J. Prod. Res. 41:16 (2003), 3689–3719.
34. Kusumastuti, R.D., Piplani, R., Hian Lim, G., Redesigning closed-loop service network at a computer manufacturer: a case study. Int. J. Prod. Econ. 111:2 (2008), 244–260.
35. Liu, H., Wang, W., Zhang, Q., Multi-objective location-routing problem of reverse logistics based on GRA with entropy weight. Grey Syst.: Theory Appl. 2:2 (2012), 249–258.
36. Lee, J.E., Gen, M., Rhee, K.-G., Network model and optimization of reverse logistics by hybrid genetic algorithm. Comput. Ind. Eng. 56:3 (2009), 951–964.
37. Mahnam, M., Yadollahpour, M.R., Famil-Dardashti, V., Hejazi, S.R., Supply chain modeling in uncertain environment with bi-objective approach. Comput. Ind. Eng. 56:4 (2009), 1535–1544.
38. Matsumoto, M., Umeda, Y., An analysis of remanufacturing practices in Japan. J. Remanuf. 1:1 (2011), 1–11.
39. Mendelson, H., Pillai, R.R., Industry clockspeed: measurement and operational implications. Manuf. Serv. Oper. Manag. 1:1 (1999), 1–20.
40. Mitra, S., Revenue management for remanufactured products. Omega 35:5 (2007), 553–562.
41. Özkır, V., Başlıgil, H., Multi-objective optimization of closed-loop supply chains in uncertain environment. J. Clean. Prod. 41 (2013), 114–125.
42. Paksoy, T., Bektaş, T., Özceylan, E., Operational and environmental performance measures in a multi-product closed-loop supply chain. Transp. Res. Part E: Logist. Transp. Rev. 47:4 (2011), 532–546.
43. Pishvaee, M.S., Farahani, R.Z., Dullaert, W., A memetic algorithm for bi-objective integrated forward/reverse logistics network design. Comput. Oper. Res. 37:6 (2010), 1100–1112.
44. Pishvaee, M.S., Kianfar, K., Karimi, B., Reverse logistics network design using simulated annealing. Int. J. Adv. Manuf. Technol. 47:1 (2009), 269–281.
45. Pishvaee, M.S., Torabi, S.A., A possibilistic programming approach for closed-loop supply chain network design under uncertainty. Fuzzy Sets Syst. 161:20 (2010), 2668–2683.
46. Qiang, Q., Ke, K., Anderson, T., Dong, J., The closed-loop supply chain network with competition, distribution channel investment, and uncertainties. Omega 41:2 (2013), 186–194.
47. Quariguasi-Frota-Neto, J., Bloemhof, J., An analysis of the eco-efficiency of remanufactured personal computers and mobile phones. Prod. Oper. Manag. 21:1 (2012), 101–114.
48. Reh, L., Challenges for process industries in recycling. China Particuology 4:2 (2006), 47–59.
49. Sahni, S., Boustani, A., Gutowski, T.G., Graves, S.C., 2010. Engine remanufacturing and energy savings. MIT Energy Initiative Report (MITEI-1-d−2010).
50. Shankar, B.L., Basavarajappa, S., Chen, J.C.H., Kadadevaramath, R.S., Location and allocation decisions for multi-echelon supply chain network – A multi-objective evolutionary approach. Expert Syst. Appl. 40:2 (2013), 551–562.
51. Soleimani, H., Seyyed-Esfahani, M., Shirazi, M.A., Designing and planning a multi-echelon multi-period multi-product closed-loop supply chain utilizing genetic algorithm. Int. J. Adv. Manuf. Technol. 68:4 (2013), 917–931.
52. Souza, G.C., Closed-loop supply chains: a critical review, and future research. Decis. Sci. 44:1 (2013), 7–38.
53. Souza, G.C., Product disposition decisions on closed-loop supply chains. Boone, T., Jayaraman, V., Ganeshan, R., (eds.) Sustainable Supply Chains, 2012, Springer, New York, 149–164, 10.1007/978-1-4419-6105-1.
54. Srivastava, S., Network design for reverse logistics. Omega 36:4 (2008), 535–548.
55. Stock, J., T., Speh, H.S., Many happy (product) returns. Harv. Bus. Rev. 80:7 (2002), 16–17.
56. Sutherland, J.W., Adler, D.P., Haapala, K.R., Kumar, V., A comparison of manufacturing and remanufacturing energy intensities with application to diesel engine production. Cirp. Ann.-Manuf. Technol. 57:1 (2008), 5–8.
57. Tiwari, M.K., Chang, P.C., Choudhary, A., Carbon-efficient production, supply chains and logistics. Int. J. Prod. Econ. 164 (2015), 193–196, 10.1016/j.ijpe.2015.02.008.
58. Trelea, I.C., The particle swarm optimization algorithm: convergence analysis and parameter selection. Inf. Process. Lett. 85:6 (2003), 317–325.
59. Wang, H.-F., Hsu, H.-W., A closed-loop logistic model with a spanning-tree based genetic algorithm. Comput. Oper. Res. 37:2 (2010), 376–389.
60. Ye, F., Zhao, X., Prahinski, C., Li, Y., The impact of institutional pressures, top managers׳ posture and reverse logistics on performance—evidence from China. Int. J. Prod. Econ. 143:1 (2013), 132–143.
61. Yong-ling Zheng, Long-Hua Ma, Li-yan Zhang, Ji-xin Qian, 2003. On the convergence analysis and parameter selection in particle swarm optimization. In: Proceedings of the 2003 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.03EX693). IEEE, 3. pp. 1802–1807.
62. Zhang, T., Chu, J., Wang, X., Liu, X., Cui, P., Development pattern and enhancing system of automotive components remanufacturing industry in China. Resour. Conserv. Recycl. 55:6 (2011), 613–622.