计算机集成制造系统 ›› 2018, Vol. 24 ›› Issue (第11): 2879-2888.DOI: 10.13196/j.cims.2018.11.022

• 当期目次 • 上一篇    下一篇

基于顾客点分布的自提点逐渐覆盖选址模型

周翔,许茂增+,吕奇光   

  1. 重庆交通大学经济与管理学院
  • 出版日期:2018-11-30 发布日期:2018-11-30
  • 基金资助:
    国家自然科学基金资助项目(71471024);重庆市教育委员会科学技术研究资助项目(KJ1705116)。

Pickup point gradual covering location model based on customer-points' distribution

  • Online:2018-11-30 Published:2018-11-30
  • Supported by:
    Project supported by the National Natural Science Foundation,China(No.71471024),and the Science and Technology Research Program of Chongqing Education Commission,China(No.KJ1705116).

摘要: 为了研究网络零售配送中基于顾客点分布的自提点数量和位置的集成选址问题。根据顾客点的分布设计网格动态密度聚类算法,确定自提点的选址数量和备选位置;然后建立以顾客满意度和最大覆盖为双目标的自提点逐渐覆盖选址模型来实现自提点选址。在IBM CPLEX中对算例进行求解,验证了算法和模型的有效性,同时根据计算结果提出两种适用于网络零售配送的自提点选址策略。

关键词: 自提点, 网格密度, 聚类算法, 顾客满意度, 最大覆盖选址模型

Abstract: To research the integrated location problem of number and position of pickup points based on the customer-points distribution in E-retailing distribution model,according to the distribution of customer-points,the grid dynamic density clustering algorithm was designed to determine the number and the alternative locations of pickup points.The model of pickup point location was established with the customer satisfaction and the gradually maximal covering as the bi-objective.The case was solved in IBM CPLEX,and the results verify the effectiveness of the algorithm and model,and two pickup point location strategies were proposed for E-retailing distribution with the calculation results.

Key words: pickup point, grid density, clustering algorithm, customer satisfaction, maximal covering location model

中图分类号: