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An efficiency sorting multi-objective optimization framework for sustainable supply network optimization and decision making

delete2020-11-01
delete15
PRE
AI
Y
Yadong Wang *
Q
Quan Shi
Q
Qiwei Hu
Z
Zhifeng You
Y
Yongsheng Bai
C
Chiming Guo
DOI:10.1016/j.jclepro.2020.122842delete
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摘要

摘要

En 中文
This paper attempts to make optimization and decision on the sustainable supply network (SSN) with the consideration of the overall performance of the network from economic, environmental, and social aspects. A multi-objective optimization model was developed and an efficiency sorting multi-objective optimization framework is proposed to solve the model. In the framework, an efficiency sorting strategy is integrated with the multi-objective optimization algorithms (MOOAs). The efficiencies, calculated by improved data envelopment analysis (DEA), can fully reflect the overall performance of the SSN, as well as, guide the evolution of the MOOAs. To verify the effectiveness of the model and algorithms, four MOOAs and two sorting strategies are combined in pairs and tested on a case study. Experimental results demonstrate that, with the proposed framework, decision makers can not only obtain the feasible Pareto optimal solutions but also can select the optimal one from these Pareto solutions based on their efficiency. (C) 2020 Elsevier Ltd. All rights reserved.
Keyword:
Sustainable supply network
Closed-loop network
Multi-objective optimization
Data envelopment analysis (DEA)
Decision making
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期刊

Journal of Cleaner Production 封面图
Journal of Cleaner Production
IF:
10
论文数:
4.7W
被引数:
36.8W

机构

A
Army Engineering University of PLA
学者数:
5.0K
论文数: 3.7K
被引数: 5
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