基于共同配送的农村快递车辆调度问题  

Rural Express Vehicle Scheduling Problems Based on Joint Distribution

作　　者：石永强[1] 郭铎 张智勇[1] SHI Yong-qiang;GUO-Duo;ZHANG Zhi-yong(School of Economics and Commerce,South China University of Technology,Guangzhou 510006,China)

机构地区：[1]华南理工大学经济与贸易学院,广东广州510006

出　　处：《交通运输研究》2021年第2期20-27,共8页Transport Research

基　　金：国家自然科学基金面上项目(71572058)。

摘　　要：为降低农村物流成本,助力“快递下乡”工程的实施,在考虑重量、体积、订单、路径等约束条件下,以总利润最大化为目标构建基于共同配送模式的农村快递车辆调度模型;并提出采用基于随机修复非可行解策略的遗传算法求解该模型,同时在算法中引入多种群机制以提高求解的效率和效果。最后,结合实际算例对模型进行验证;设计不同订单规模的仿真算例对算法性能进行分析。研究结果表明:共同配送策略能从全局优化的角度合理配置区域内物流资源,与独立配送模式相比可降低30%的配送成本。仿真实验表明:相较于标准遗传算法,改进遗传算法能快速地搜索到更优的满意解,可以有效求解共同配送模式下的农村快递车辆调度问题。In order to reduce rural logistics costs and promote the implementation of the"express to the countryside"project,a rural express vehicle scheduling model with the goal of maximizing the total profits which considered the constraints of weight,volume,order,departure and path,was proposed.Besides,a genetic algorithm based on random repair infeasible solution strategy was proposed to solve the model,and a multi population mechanism was introduced to improve the efficiency and effect of the algorithm.Finally,the model was verified by a practical example,and the algorithm performance was analyzed by the simulation examples of different scales.The results show that the joint distribution strategy effectively optimizes all regional logistics resources and reduces the logistics cost by 30%compared with the separate distribution scheme.In addition,computational results show that,compared with the standard genetic algorithm,the improved genetic algorithm can quickly find a better satisfactory solution,and can effectively solve the rural express vehicle scheduling problem with the joint distribution mode.

关 键 词：农村快递物流 共同配送 车辆调度 0-1整数规划 多种群遗传算法 

分 类 号：U4-9[交通运输工程—道路与铁道工程] F259.2[经济管理—国民经济]