A Novel Sustainable Closed-loop Supply Chain Network Design by Considering Routing and Quality of Products

Authors

College of Engineering, Department of Industrial Engineering, Shahed University, Tehran, Iran

Abstract

One of the strategic decisions that can be made in supply chain is designing its network which has high impact on costs, and satisfaction level of customers. This paper focuses on designing a distribution network including determining the number and location of facilities, how to allocate the customers in network, and also determining the extent of carrying different products from different origins to different destinations; in this distribution network, according to the existing restrictions, customer demand is considered at minimum cost. In addition to secondary chain and reuse market as a retrieval option, model flexibility in defining quality and routing-locating is also among the innovation points of the model. Firstly, in forward chain the model consists of supplier, manufacturer, warehouse, distributor, and customer. In reverse chain, the model includes reuse market, secondary supply chain, collection, reprocess and disposal centers. The model could be generalized to industries with various strategies. Secondly, a sensitivity analysis was performed on a numerical example; also the non-dominated sorting algorithm (NSGA II) was used for a large-sized sample; which its performance was measured by analysis of variance (ANOVA) test. The results show that, returned products with average quality lead to lower costs and higher social benefits; and meta-heuristic NSGA II method is efficient. Because, it creates business opportunities and leads to less economic and environmental costs.

Keywords


1.     Moshtagh, M.S., and Taleizadeh, A.A., “Stochastic integrated manufacturing and remanufacturing model with shortage, rework and quality based return rate in a closed loop supply chain”, Journal of Cleaner Production,  Vol. 141, No. 141, (2017), 1548–1573.
2.     Wong, C.W.Y., Lai, K.H., Lun, Y.H. V, and Cheng, T.C.E., Environmental management: the supply chain perspective, Springer, (2015).
3.     Tseng, M.L., Wu, K.J., Hu, J., and Wang, C.H., “Decision-making model for sustainable supply chain finance under uncertainties”, International Journal of Production Economics,  Vol. 205, (2018), 30–36.
4.     Bastas, A., and Liyanage, K., “Sustainable supply chain quality management: A systematic review”, Journal of cleaner production,  Vol. 181, (2018), 726–744.
5.     Chopra, V.S., and Meindl, P., “Supply Chain Management. Strategy, Planning & Operation”, Gabler, Wiesbaden, (2007), 265–275.
6.     Seifbarghi, M., Bozorgi-Amiri, A., Rahmani-Ahranjani, A., and Najafi, E., “Managing Environmentally Conscious in Designing Closed-loop Supply Chain for the Paper Industry”, International Journal of Engineering - Transactions A: Basics,  Vol. 30, No. 7, (2017), 1038–1047.
7.     Tavakkoli-Moghaddam, R., Yadegari, M., and Ahmadi, G., “Closed-loop Supply Chain Inventory-location Problem with Spare Parts in a Multi-Modal Repair Condition”, International Journal of Engineering - Transactions B: Applications,  Vol. 31, No. 2, (2018), 346–356.
8.     Soysal, M., “Closed-loop Inventory Routing Problem for returnable transport items”, Transportation Research Part D: Transport and Environment,  Vol. 48, No. 48, (2016), 31–45.
9.     Govindan, K., Soleimani, H., and Kannan, D., “Reverse logistics and closed-loop supply chain: A comprehensive review to explore the future”, European Journal of Operational Research,  Vol. 240, No. 3, (2015), 603–626.
10.   Govindan, K., and Soleimani, H., “A review of reverse logistics and closed-loop supply chains: a Journal of Cleaner Production focus”, Journal of Cleaner Production,  Vol. 142, No. 142, (2017), 371–384.
11.   Zareian Jahromi, H., Fallahnezhad, M.S., Sadeghieh, A., and Ahmadi Yazdi, A., “A Robust Multi Objective Optimization Model for Sustainable Closed-Loop Supply Chain Network Design”, Journal of Industrial Engineering Research in Production Systems,  Vol. 02, No. 3, (2014), 93–111.
12.   Masoudipour, E., Amirian, H., and Sahraeian, R., “A novel closed-loop supply chain based on the quality of returned products”, Journal of Cleaner Production,  Vol. 151, (2017), 344–355.
13.   Martínez-Salazar, I.A., Molina, J., Ángel-Bello, F., Gómez, T., and Caballero, R., “Solving a bi-objective Transportation Location Routing Problem by metaheuristic algorithms”, European Journal of Operational Research,  Vol. 234, No. 1, (2014), 25–36.
14.   Garg, K., Kannan, D., Diabat, A., and Jha, P.C., “A multi-criteria optimization approach to manage environmental issues in closed loop supply chain network design”, Journal of Cleaner Production,  Vol. 100, (2015), 297–314.
15.   Maiti, T., and Giri, B.C., “Two-way product recovery in a closed-loop supply chain with variable markup under price and quality dependent demand”, International Journal of Production Economics,  Vol. 183, No. 183, (2017), 259–272.
16.   Sadegheih, A., Drake, P.R., Li, D., and Sribenjachot, S., “Global Supply Chain Management under Carbon Emission Trading Program Using Mixed Integer Programming and Genetic Algorithm”, International Journal of Engineering - Transactions B: Applications,  Vol. 24, No. 1, (2010), 37–53.
17.   Barbosa-Póvoa, A., Silva, C. da, and Carvalho, A., “Opportunities and challenges in sustainable supply chain: An operations research perspective”, European Journal of Operational Research,  Vol. 268, No. 2, (2018), 399–431.
18.   Reefke, H., and Sundaram, D., “Sustainable supply chain management: Decision models for transformation and maturity”, Decision Support Systems,  Vol. 113, (2018), 56–72.
19.   Chen, D.S., Batson, R.G., and Dang, Y., Applied integer programming: modeling and solution, John Wiley & Sons, Inc., USA, (2011).
20.   Jeihoonian, M., Kazemi Zanjani, M., and Gendreau, M., “Closed-loop supply chain network design under uncertain quality status: Case of durable products”, International Journal of Production Economics,  Vol. 183, (2017), 470–486.
21.   Mavrotas, G., “Effective implementation of the ε-constraint method in Multi-Objective Mathematical Programming problems”, Applied Mathematics and Computation,  Vol. 213, No. 2, (2009), 455–465.