考虑需求可拆分的多车型电动车路径优化研究  

Research on the Multi-vehicle Electric Vehicle Path Optimization Considering Split Demand

作　　者：袁艳华 李美燕[1] 赵萍萍 YUAN Yanhua;LI Meiyan;ZHAO Pingping(Shandong University of Science and Technology,Qingdao 266590,China)

机构地区：[1]山东科技大学,山东青岛266590

出　　处：《物流科技》2025年第5期19-23,共5页Logistics Sci Tech

基　　金：2021年度山东省重点研发计划(软科学)项目“山东省工业互联网发展趋势和对策研究”(2021RZB02007)。

摘　　要：为降低J公司的物流配送成本,提高运输效率,提出考虑需求可拆分的多车型电动车路径优化方案,以车辆固定成本、能耗成本、时间窗惩罚成本和碳交易成本之和最小化为目标建立优化模型,并采用改进的自适应遗传算法进行求解,得到优化后的配送方案。与优化前同车型配送方案相比,总成本降低了8.4%,配送时长缩短了11.5%,有效地降低了企业的成本,提高了物流配送效率和客户满意度。In order to reduce the logistics and distribution cost of company J and improve the transportation efficiency,an optimization scheme for multi-vehicle electric vehicle path considering the demand can be split is proposed,and the optimization model is established with the goal of minimizing the sum of vehicle fixed cost,energy consumption cost,time window penalty cost and carbon transaction cost,and the improved adaptive genetic algorithm is used to solve the optimized distribution scheme.Compared with the distribution scheme of the same model before optimization,the total cost has been reduced by 8.4%,and the delivery time has been shortened by 11.5%,which effectively reduces the cost of the enterprise and improves the logistics and distribution efficiency and customer satisfaction.

关 键 词：物流配送 需求可拆分 多车型 电动车 改进的自适应遗传算法 

分 类 号：U116.2[交通运输工程]