众包物流任务分派优化方法研究  

Research on Optimization Methodof Crowdsourcing Logistics Task Assignment

作　　者：温国锋[1] 刘文娇 李兆隆 WEN Guo-feng;LIU Wen-jiao;LI Zhao-long(Shandong Technology and Business University,Yantai 264005,China)

机构地区：[1]山东工商学院管理科学与工程学院,山东烟台264005

出　　处：《山东工商学院学报》2023年第3期55-65,共11页Journal of Shandong Technology and Business University

基　　金：教育部人文社会科学研究项目“韧性视角下‘交通-物流’关联基础设施系统应急响应的影响因素研究”(21YJCZH077)。

摘　　要：针对众包物流参与最后一公里交付的任务分派问题,首先,考虑司机绕行派送任务产生的费用,以及其派送任务的多寡因素计算司机的派送报酬。随后,提出以最小化派送成本为目标的众包物流任务分派问题,建立该问题的整数规划模型。再次,利用改进后的禁忌搜索算法对问题进行求解。该算法采用自适应并行算法构造初始解,为提高寻找最优解的效率,利用多种邻域搜索方法获得候选解。最后,采用Solomon基准测试实例进行数值实验,实验结果表明所设计的算法对求解本文模型是有效的。小规模实验中,对比TS算法和lingo的结果验证了算法的有效性;在大中规模实验中,所构建模型能高效的将任务分派给司机,且能得到较高的众包接受率和包裹分派率。In view of the task assignment problem of crowdsourcing logistics participating in the last kilometer delivery.Firstly,the cost of the driver bypassing the dispatch task and the number of its dispatch task are considered to calculate the driver's dispatch reward.Secondly,the crowdsourcing logistics task assignment problem aiming at minimizing the delivery cost is proposed,and the integer programming model of the problem is established.Thirdly,the improved tabu search algorithm is used to solve the problem.In order to improve the efficiency of finding the optimal solution,a variety of neighborhood search methods are used to obtain the candidate solution.Finally,numerical experiments are carried out with a Solomon benchmark example.The experimental results show that the designed algorithm is effective for solving the model.In small-scale experiments,the results of TS algorithm and lingo are compared to verify the effectiveness of the algorithm;In large and medium-sized experiments,the model can efficiently assign tasks to drivers,and can get high crowdsourcing acceptance rate and package distribution rate.

关 键 词：众包物流 任务分派 优化模型 禁忌搜索算法 

分 类 号：F259.2[经济管理—国民经济]