计算机应用 ›› 2019, Vol. 39 ›› Issue (2): 604-610.DOI: 10.11772/j.issn.1001-9081.2018061318

• 应用前沿、交叉与综合 • 上一篇    下一篇

考虑客户聚类与产品回收的两级闭环物流网络选址路径优化

梁喜, 凯文   

  1. 重庆交通大学 经济与管理学院, 重庆 400074
  • 收稿日期:2018-06-25 修回日期:2018-08-25 出版日期:2019-02-10 发布日期:2019-02-15
  • 通讯作者: 梁喜
  • 作者简介:梁喜(1978-),男,江苏连云港人,教授,博士,主要研究方向:物流与供应链管理、交通运输经济;凯文(Kevin Assogba)(1991-),男,贝宁人,硕士研究生,主要研究方向:物流与供应链管理。

Two-echelon closed-loop logistics network location-routing optimization based on customer clustering and product recovery

LIANG xi, Kevin Assogba   

  1. School of Economics and Management, Chongqing Jiaotong University, Chongqing 400074, China
  • Received:2018-06-25 Revised:2018-08-25 Online:2019-02-10 Published:2019-02-15

摘要: 针对目前不合理的废旧产品回收以及物流活动产生的碳排放污染,提出了一种考虑客户聚类与产品回收的两级闭环物流网络选址-路径优化模型。首先,结合实际物流网络的动态性假设客户需求量和回收率的不确定性特征,以最小运营成本和最小环境影响为目标建立选址-路径优化模型;其次,对多目标进化算法进行改进,提出了考虑客户聚类结果的两级物流设施选址-路径问题求解算法;最后,对该优化算法进行算法性能分析,并以重庆市某企业为例进行了模型和算法验证。结果表明,所建立的模型和算法能有效降低决策难度并提高物流系统的运作效率,所求出的优化方案能减少物流运作成本和降低物流运输过程对环境的影响。

关键词: 闭环物流, 选址-路径优化, 产品回收, 客户聚类, 遗传算法

Abstract: With regard to unreasonable waste collection and considerable environmental pollution due to logistics activities, a two-echelon closed-loop logistics network location-routing optimization model based on customer clustering and product recovery was proposed. Firstly, considering the dynamic nature of actual logistics network, the uncertain characteristics of customer demand and recovery rate were assumed, and location-routing optimization model based on minimum operating cost and minimum environmental impact was established. Secondly, based on improvement of multi-objective evolutionary algorithm, an algorithm for two-echelon closed-loop logistics network location-routing optimization model based on customer clustering and product recovery was proposed. Finally, the performance of the proposed optimization algorithm was analyzed and a practical experimentation of model and algorithm was conducted on the location-routing problem of a company in Chongqing city. Analyses show that the proposed model and algorithm can alleviate the final decision difficulty and improve operational efficiency of the logistics system while the optimization scheme obtained can reduce total cost and environmental impact.

Key words: closed-loop logistics, location-routing optimization, product recovery, customer clustering, genetic algorithm

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