Benders decomposition algorithm for a green closed-loop supply chain under a build-to-order environment

Document Type : IIEC 2020

Authors

School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran

Abstract

Nowadays, researches pay more attention to environmental concerns consisted of various communities. This study proposes a multi-echelon, multi-period closed-loop supply chain (CLSC). A comprehensive model considers the selection of selection of technology and environmental effects. The supply chain is under a build-to-order (BTO) environment. So, there is not a final product inventory. Also, the returned products disassembled into reused components. The bi-objective mixed-integer linear problem is solved by a Benders decomposition algorithm by validating some numerical experiments. The convergence is also shown in the property.

Keywords

Main Subjects


 
Domiguez, R., Ponte, B., Cannella, S. and Framinan, J. M. (2019). On the dynamics of closed-loop supply chains with capacity constraint. Computers & Industrial Engineering, 128; 91-103.
 
Ebrahimi, M., and Tavakkoli-Moghaddam‎, R. (2020). A build to order green supply chain problem by concidering the technology, Proceeding of the 16th Iranian Internatioal Engineering Conference, Tehran, Iran, 22-23 January 2020.
 
Jabbarzadeh, A., Haughton, M. and Khosrojerdi, A. (2018). Closed-loop supply chain network design under disruption risks: a robust approach with real world application. Computers & Industrial Engineering, 116; 178-191.
 
Ebrahimi, M., Tavakkoli-Moghaddam and R., Joli, F. (2018). Bi-objective build-to-order supply chain problem with customer utility. IJE Transactions A: Basics, 31; 1066-1073.
 
Ebrahimi, M., Tavakkoli-Moghaddam and R., Joli, F. (2019). Benders decomposition algorithm for a build-to-order supply chain problem under uncertainty. International Journal of Industrial Engineering & Production Research, 30; 173-186.
 
Gaur, J. and Mani, V. (2018). Antecedents of closed-loop supply chain in emerging economics: A conceptual framework using stakeholderʼs perspective. Resources, Conservation & Recycling, 139; 219-227.
 
Howang, C. L., Paius S. R., Yoon, K. and Masud, A. S. M. (1980). Mathematical programming withmultiple objectives: a tutorial. Computer & Operations Research, 7(1-2); 5-31.
 
Hassanpour, A., Bgherinejad, J. and Bashiri, M. (2019). A robust leader-follower approach for closed loop supply chain network design considering returns quality levels. Computers & Industrial Engineering, 136; 293-304.
 
Khalafi, S., Hafezalkotob, A., Mohammaditabar, D. and Sayadi, M. K., (2019). A novel model for a network of a closed-loop supply chain with recycling of returned perishable goods: a case study of dairy industry. Journal of Industrial and System Engineering, 12(4);136-153.
   
Liu, Z., Li, K. W., Li, B. Y., Huang, J. and Tang, J. (2019). Impact of product design strategies on the operations of a closed-loop supply chain. Transportation Research Part E, 124; 75-91.
 
Laimazloumian, M., Wong, K.Y., Govindan, K. and Kannan, D. (2013). A robust optimization model for agile and build-to-order supply chain planning under uncertainties. Annals of Operations Research, 240; 435-470.
 
Ma, R., Yao, L., Jin, M., Ren, P. and LV, Z. (2016). Robust environmental closed-loop supply chain design under uncertainty. Chaos, Solitons & Fractals, 89; 195-202.
 
Mardan, E., Govindan, K., Mina, H. and Golami-Zanjani, S. M. (2019). An accelerated benders decomposition algorithm for a bi-objective green closed-loop supply chain network design problem. Journal of Cleaner Production, 235; 1499-1514.
 
Pishvaee, M. S., Razmi, J. and Torabi, S. A. (2014). An accelerated benders decomposition algorithm for sustainable supply chain network design under uncertainty: a case study of medical needle and syringe supply chain. Transportation Research Part E, 67; 14-38.
 
Salehi, H., Tavakkoli-Moghaddam, R., Taleizaheh, A. A., and Hafezalkotob, A. (2019). Solving a Location-Alocation problem by a fuzzy self-adaptive NSGA-II. Journal of Industrial and Systems Engineering, 12(4); 18-26.
 
Sadeghi Rad, R. and Nahavandi, N. (2018). A novel multi-objective optimization model for integrated problem of green closed-loop supply chain network design and quantity discount. Journal of Cleaner Production, 196; 1549-1565.
 
Schankel, M., Kirikke, H., Caniels, M. C. J. and Lumbrechts, W. (2019). Vicious cycles that hinder value creation in closed loop supply chain: experiences from the field. Journal of Cleaner Production, 223; 278-288.
 
Shaharudin, M. R., Tan, K. C., Kannan and V., Zailani, S. (2019). The mediating effects of products returns on the relationship between green capabilities and closed-loop supply chain adoption. Journal of Cleaner Production, 211, 233-246.
 
Shimada, T. and Van Wassenhove, L. N. (2019). Closed-loop supply chain activities in Japanese home appliance/personal computer manufacturers: a case study. International Journal of Production Economics, 212; 259-265.
 
Wan, N. and Hong, D. (2019). The impacts of subsidy policies and transfer pricing policies on the closed-loop supply chain with dual collection channels. Journal of Cleaner Production 224; 881-891.
 
Wang, Y., Li, B., Wang, Z., Liu, Z., Zhu, X. and Wang, Q. (2019). Closed-loop supply chain models with product recovery and donation. Journal of Cleaner Production, 227; 861-876.  
 
Zhen, L., Huang, L. and Wang, W. (2019). Green and sustainable closed-loop supply chain network design under uncertainty. Journal of Cleaner Production, 227; 1195-1209.
 
Yavari, M. and Geraeli, M. (2019). Heuristic method for robust optimization model for green closed-loop supply chain network design of perishable goods. Journal of Cleaner Production, 226; 282-305.
 
Yousefi, Nejad Attari, M. and Ebadi Torkayesh, A. (2018). Developing benders decomposition algorithm for a green supply chain network of mine industry: case of Iranian industry. Operations Research Perspectives, 5; 371-382.