An efficiency sorting multi-objective optimization framework for sustainable supply network optimization and decision making. (1st November 2020)

• Record Type: Journal Article
• Authors: Wang, Yadong; Shi, Quan; Hu, Qiwei; You, Zhifeng; Bai, Yongsheng; Guo, Chiming
• Is Part Of: Journal of cleaner production. Volume 272(2020)
• Publication Date: 2020-11-01
• Subjects: Sustainable supply network -- Closed-loop network -- Multi-objective optimization -- Data envelopment analysis (DEA) -- Decision making; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2020.122842
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: 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.