Fourth party logistics routing problem considering stochastic demand and multiple transportation modes

被引：0

作者：

Lu F. ^{[1
,2
]}

Chen W. ^{[2
]}

Bi H. ^{[1
]}

Wang S. ^{[1
]}

机构：

[1] School of Economics and Management, Yanshan University, Qinhuangdao

[2] School of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao

来源：

Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2020年 / 26卷 / 10期

基金：

中国国家自然科学基金;

关键词：

Fourth party logistics; Genetic algorithms; Multiple transportation modes; Routing problem; Stochastic demand;

D O I：

10.13196/j.cims.2020.10.025

中图分类号：

学科分类号：

摘要：

Aiming at problem that customers demand is characterized by timeliness and regularity in Fourth Party Logistics (4PL), the Fourth Party Logistics Routing Problem (4PLRP) with stochastic demand and multiple transportation modes were researched by combining with the multiple transportation modes provided Third Party Logistics (3PL) providers in reality. With the condition that customer demand was random variable, the chance constrained program model was designed with the goal of minimizing transportation costs, which determined the transportation modes while selecting transportation routes and logistics 3PL providers. To solve the model, an Improved Genetic Algorithm (IGA) with embedded migration operator and elite strategy was designed. The algorithm parameters optimized by Taguchi experiments effectively improve the accuracy of solutions. The experimental results showed that with stochastic demand of customers, the transportation cost increased with the different confidence level, and joint transportation through multiple transportation modes could overcome the defects of single transportation mode and effectively reduce the transportation cost. The proposed algorithm had better global search capability and computational accuracy, and the IGA could solve the problem effectively. © 2020, Editorial Department of CIMS. All right reserved.

引用

页码：2864 / 2876

页数：12

共 31 条

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