A Bi-Objective Reverse Logistics Network Design Under the Emission Trading Scheme

被引：21
|
作者：
Yuchi, Qunli [1 ,2 ]
Wang, Nengmin [1 ,2 ]
Li, Shuang [1 ,2 ]
Yang, Zhen [1 ,2 ]
Jiang, Bin [3 ]
机构：
[1] Xi An Jiao Tong Univ, Sch Management, Xian 710049, Shaanxi, Peoples R China
[2] Xi An Jiao Tong Univ, Key Lab, Minist Educ Proc Control & Efficiency Engn, Xian 710049, Shaanxi, Peoples R China
[3] DePaul Univ, Driehaus Coll Business, Dept Management, Chicago, IL 60604 USA
来源：
IEEE ACCESS | 2019年 / 7卷
基金：
中国国家自然科学基金;
关键词：
Carbon footprint; emission trading scheme; network design; NSGA-II; reverse logistics; GENETIC ALGORITHM APPROACH; SUPPLY CHAIN; MULTIOBJECTIVE OPTIMIZATION; CARBON FOOTPRINTS;
D O I：
10.1109/ACCESS.2019.2898213
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In general, reverse logistics network design has been driven by a need to reduce costs and to improve customer service without considering its environmental impact. In this paper, we address a reverse logistics network design problem regarding carbon emission. The problem is formulated as a bi-objective, mixed-integer, and nonlinear programming model under various operation technologies and transport modes in the truck tire remanufacturing industry. An improved non-dominated sorting genetic algorithm II (NSGA-II) solves this NP-hard problem with bi-objectives. The numerical cases demonstrate the validation of the proposed model and the advantage of improved NSGA-II over the basic NSGA-II. Furthermore, we conducted extensive sensitivity analysis, and several managerial insights are derived.
引用
收藏
页码：105072 / 105085
页数：14
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