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  • 标题:A memetic algorithm with extended random path encoding for a closed-loop supply chain model with flexible delivery
  • 本地全文:下载
  • 作者:Elham Behmanesh ; Jürgen Pannek
  • 期刊名称:Logistics Research
  • 印刷版ISSN:1865-035X
  • 电子版ISSN:1865-0368
  • 出版年度:2016
  • 卷号:9
  • 期号:1
  • 页码:1-12
  • DOI:10.1007/s12159-016-0150-y
  • 摘要:Logistics network design is a major strategic issue in supply chain management of both forward and reverse flow, which industrial players are forced but not equipped to handle. To avoid sub-optimal solution derived by separated design, we consider an integrated forward reverse logistics network design, which is enriched by using a complete delivery graph. We formulate the cyclic seven-stage logistics network problem as a NP hard mixed integer linear programming model. To find the near optimal solution, we apply a memetic algorithm with a neighborhood search mechanism and a novel chromosome representation including two segments. The power of extended random path-based direct encoding method is shown by a comparison to commercial package in terms of both quality of solution and computational time. We show that the proposed algorithm is able to efficiently find a good solution for the flexible integrated logistics network.
  • 关键词:Memetic algorithm; Closed-loop supply design; Random path; Flexible delivery
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