“自建+租赁”配送模式下的取送货车辆路径优化  

Optimization of Pick-up and Delivery Vehicle Routing Under the"Self Built and Leased"Distribution Mode

作　　者：马云峰[1,2] 杨园园 任亮[1] 陈勇超 MA Yunfeng;YANG Yuanyuan;REN Liang;CHEN Yongchao(School of Management,Wuhan University of Science and Technology,Wuhan 430065,China;不详)

机构地区：[1]武汉科技大学管理学院,湖北武汉430065 [2]武汉科技大学服务科学与工程研究中心,湖北武汉430065 [3]湖北普罗格科技股份有限公司,湖北武汉430000

出　　处：《武汉理工大学学报(信息与管理工程版)》2024年第6期887-894,共8页Journal of Wuhan University of Technology:Information & Management Engineering

基　　金：教育部人文社会科学基金项目(19YJA630054)。

摘　　要：物流企业采用自建车队配送时前期建设成本过大,车辆往返车场还会产生多余的路径成本和能源消耗。众包租赁模式虽然能减少这些成本,但是租车成本过高。为此,综合两者优势提出“自建+租赁”混合配送模式来解决取送货车辆路径问题,建立混合整数规划模型,利用自适应大邻域搜索算法对多组算例进行实验,证明了混合配送模式较单一配送模式能有效降低配送成本,减少车辆使用数量。其中,“自建+租赁”混合配送模式较传统自建车队配送模式平均优化率为5.46%;较外包配送模式平均优化率为27.43%。最后,对该模式下的自建车持有数量进行分析,得到了近似规律。When logistics companies adopt self built fleet for distribution,the initial construction cost is too large,and vehicles traveling to and from the parking lot will also generate excess path costs and energy consumption.Although crowdsourcing leasing model can reduce these costs,the car rental costs are too high.To solve the problem of the pickup and delivery vehicle routing,the article combined the advantages of both and proposed a"self built+leased"mixed distribution model.A mixed integer programming model was established,and an adaptive large neighborhood search algorithm was used to conduct experiments on multiple sets of examples.It is proved that the mixed distribution model can effectively reduce distribution costs and reduce the number of vehicles used compared to a single distribution model.Among them,the average optimization rate of the"self built+leased"mixed distribution model compared to traditional self built fleet distribution models was 5.46%;the average optimization rate was 27.43%compared with the outsourcing distribution model.Finally,the number of self-built vehicles in this model was analyzed,and the approximate law was obtained.

关 键 词：取送货 车辆路径问题 自适应大邻域搜索算法 混合配送模式 多车场 

分 类 号：O221.1[理学—运筹学与控制论] U116.2[理学—数学]