文章基本信息

标题：A Modal Interval Based Genetic Algorithm for Closed-loop Supply Chain Network Design under Uncertainty
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作者：Min Huang ; Pengxing Yi ; Lijun Guo 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2016
卷号：49
期号：12
页码：616-621
DOI：10.1016/j.ifacol.2016.07.743
语种：English
出版社：Elsevier
摘要：This paper proposes a modal interval based genetic algorithm to solve the closed-loop supply chain network configuration puzzle under uncertainty. In this special network, the retailer dominates the collection and remanufacturing activities, and sets up dedicate remanufacturing centers to remanufacture the components disassembled from the end of life excavators. This paper applies the modal intervals to characterize the uncertain parameters and combine the modal interval analysis with the genetic algorithm to solve the proposed modal interval linear programming problem. Moreover, three different decision criteria are adopted to analyze the optimal decisions of the remanufacturer. The results confirm that the proposed method can successfully determine the location of different facilities and the allocation of the products and components.
关键词：closed-loop supply chainnetwork designuncertaintyremanufacturingmodal intervalgenetic algorithm