多中心半开放式城市物流异构电动车辆路径优化  

Vehicle route optimization of heterogeneous fleet electric for multicenter semi-open urban logistic

作　　者：初良勇[1,2] 王嘉宁 丁静茹 Chu Liangyong;Wang Jianing;Ding Jingru(School of Navigation,Jimei University,Xiamen Fujian 361021,China;Fujian Shipping Research Institute,Xiamen Fujian 361021,China)

机构地区：[1]集美大学航海学院,福建厦门361021 [2]福建航运研究院,福建厦门361021

出　　处：《计算机应用研究》2024年第12期3587-3594,共8页Application Research of Computers

基　　金：国家社科基金重大项目(23&ZD138)。

摘　　要：随着国家政策的推动及新能源技术的发展,电动物流车在财政补贴、限行、节能环保和运营成本方面相较传统燃油车具有优势,越来越多的物流企业在城市配送中采用电动物流车。根据异构车型电动车辆配送队伍较单一车型电动车辆配送队伍具有降低物流配送费用优势的研究,在多中心半开放式情况下,考虑客户时间窗要求及电动车辆续航里程和充电约束,构建了配送总成本最小的电动车辆物流配送路径优化模型。针对该模型特点,利用遗传算法与模拟退火相结合的混合算法进行求解。分析表明,所构建的优化模型及求解算法可以有效解决多中心半开放式的异构电动物流配送车辆路径优化问题。With the promotion of national policies and the development of new energy technologies,this paper aimed to explore the application of electric logistics vehicles in urban distribution to optimize their routing and reduce total distribution costs.It constructed a logistics distribution path optimization model for electric vehicles that minimized total distribution costs,considering customer time window requirements,low electric vehicle range,and charging constraints.It used a hybrid algorithm combining genetic algorithm and simulated annealing to solve the model.The analysis shows that the constructed optimization model and the solution algorithm can effectively solve the path optimization problem for heterogeneous electric logistics distribution vehicles in a multi-center,semi-open environment.The proposed model and algorithm not only reduce total distribution costs but also enhance the efficiency of electric logistics vehicles in urban distribution,demonstrating practical application value.

关 键 词：车辆路径问题 异构车型 电动物流 遗传-模拟退火算法 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]