A novel multi-objective model for green forward and reverse logistics network design

被引:114
|
作者
Zarbakhshnia, Navid [1 ]
Soleimani, Hamed [2 ]
Goh, Mark [3 ,4 ]
Razavi, Seyyedeh Sara [5 ]
机构
[1] IAU, Qazvin Branch, Young Researchers & Elites Club, Qazvin, Iran
[2] IAU, Qazvin Branch, Fac Ind & Mech Engn, Dept Ind Engn, Qazvin, Iran
[3] Natl Univ Singapore, NUS Business Sch, Singapore, Singapore
[4] Natl Univ Singapore, Logist Inst Asia Pacific, Singapore, Singapore
[5] Islamic Azad Univ, Qazvin Branch, Dept Ind Management, Fac Management & Accounting, Qazvin, Iran
关键词
Supply chain management; Green forward and reverse logistics; Multi-objective programming; CO2; emissions; Epsilon-constraint method; LOOP SUPPLY CHAIN; CLOSED-LOOP; IMPLEMENTATION; COLLECTION; DECISIONS; CHANNEL; WASTE;
D O I
10.1016/j.jclepro.2018.10.138
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
With a greater awareness of responsibility for the environment and the need to sustain profitability in a competitive market, reverse logistics has become a key part of supply chain management. This paper therefore seeks to consider the designing and planning of a green forward and reverse logistics network, through a mixed integer linear programming model. The model is applied to a multi-stage, multiproduct, and multi-objective problem whereby the first objective is to minimize the cost of operations, processes, transportation, and fixed costs of the establishment. The second objective is to minimize the amount of CO2 emissions based on the gram unit, while the third is to optimize the number of machines in the production line. For validation, the model is applied to the home appliance industry through several test problems. In terms of the solution methodology, an epsilon-constraint method is developed as the area of optimization in order to obtain a set of Pareto solutions. Finally, sensitivity analysis is conducted to understand the effects of changes in the demand, cost, and rate of return of the used product, on the objective function values. (C) 2018 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1304 / 1316
页数:13
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