基于顾客满意度的网购物流配送路径优化研究  

Research on Optimization of Online Shopping Logistics Distribution Route Based on Customer Satisfaction

作　　者：张颖[1] 王琦 ZHANG Ying;WANG Qi(School of Science,Shenyang University of Technology,Shenyang 110870,China)

机构地区：[1]沈阳工业大学理学院,沈阳110870

出　　处：《湖北民族大学学报（自然科学版）》2022年第2期226-231,共6页Journal of Hubei Minzu University:Natural Science Edition

基　　金：辽宁省科学技术计划项目(2019JH1/10100028).

摘　　要：针对服务范围广、需求复杂多变的网购物流配送模式,综合考虑区块链技术优势和网购物流的特点,构建基于顾客满意度的动态需求车辆路径优化模型,并设计遗传算法进行实例仿真检验模型的有效性与适用性.结果表明:该模型基于在沿途候补配送中心补货的策略,有效降低了往返配送中心补货的频次,节约了配送时间,从而为提高网购物流顾客满意度提供新的解决思路.Aiming at the online shopping logistics distribution model with a wide range of services,complex and changeable demand,this paper comprehensively considers the advantages of blockchain technology and the characteristics of online shopping logistics,we construct a dynamic demand vehicle path optimization model based on customer satisfaction,and designs a genetic algorithm to simulate the effectiveness and applicability of the model.The results show that based on the strategy of replenishing at the standby distribution centers along the way,the model effectively reduces the frequency of replenishment to and from the distribution centers,saves the delivery time,and thus provides a new solution for improving the customer satisfaction of online shopping logistics.

关 键 词：网购物流 区块链技术 顾客满意度 遗传算法 路径优化 

分 类 号：O224[理学—运筹学与控制论]