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共同配送选址-路径优化模型与算法
李珍萍1, 赵雨薇1, 张煜炜1,2
1.北京物资学院 信息学院, 北京 101149;2.首都经济贸易大学 管理工程学院, 北京 101149
摘要:
以北京市奶制品配送问题为场景,研究了共同配送选址路径优化问题。建立了两层级带容量约束的共同配送选址路径问题的混合整数规划模型,设计了求解模型的三阶段算法。第一阶段采用基于遗传算法的带容量限制的K-means聚类方法,将客户划分为若干客户集;第二阶段计算每个备选配送中心为每个客户集提供服务的最优配送路径及成本,在此基础上将共同配送中心选址与第二层级配送路径优化问题简化为配送中心选址和客户集分配问题,建立数学模型并利用Lingo软件求解;第三阶段确定从物流中心到共同配送中心的最优配送路径。通过对比两大品牌奶制品在北京地区各商超的单独配送与共同配送成本,验证了模型和算法的合理性和有效性。研究结果为解决不同类型产品共同配送网络优化等问题提供了决策依据。
关键词:  共同配送  两层级选址路径问题  混合整数规划  三阶段算法  遗传算法  K-means聚类
DOI:10.11835/j.issn.1000-582X.2020.01.004
分类号:
基金项目:国家自然科学基金项目(71771028);北京市自然科学基金项目(Z180005);2018年北京市属高校高水平创新团队支持计划项目(IDHT20180510);北京市智能物流协同创新中心开放课题(BILSCIC-2018KF-09);北京物资学院校级重大课题(2019XJZD09);北京市科技创新服务能力建设-高精尖学科建设项目。
Optimization model and algorithm of location-routing for joint distribution
LI Zhenping1, ZHAO Yuwei1, ZHANG Yuwei1,2
1.School of Information, Beijing Wuzi University, Beijing 101149 P. R. China;2.School of Management Engineering, Capital University of Economics and Business, Beijing 100070 P. R. China
Abstract:
Based on the multiple dairy products distribution in Beijing, the optimization of location-routing for joint distribution was studied. A mixed integer programming model was formulated for the joint distribution location-routing problem with two-echelon capacitated constraints. A three-phase algorithm was designed for solving it. First, all customers were divided into multiple customer sets by K-means clustering method based on genetic algorithm. Then, the optimal delivery routes and costs for each candidate distribution center serving each customer set were calculated, by which the joint distribution centers location and the secondary level delivery routing problem were simplified to that of joint distribution centers location and customer sets allocation.The mathematical model was formulated, and solved by Lingo software. Finally, the first level delivery routes from the logistics center to the selected joint distribution centers were determined. By comparing the costs of separate distribution mode and joint distribution mode of two brands of dairy products in Beijing, the rationality and effectiveness of the model and algorithm were verified. It provides the decision-making basis for solving the problems such as the joint distribution network optimization of multi-brand daily products.
Key words:  joint distribution  two-echelon capacitated location-routing problem (2E-CLRP)  mixed integer programming  three-phase algorithm  genetic algorithm  K-means clustering
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