Logistics Pure Electric Vehicle Routing Based on GA-PSO Algorithm

IF 0.6 4区 工程技术 Q4 MECHANICS
Mechanika Pub Date : 2023-06-17 DOI:10.5755/j02.mech.31954
M. Wang, Qiyue Xie
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引用次数: 0

Abstract

 Abstract:Based on current energy storage technologies such as batteries and fuel cells, the inherent battery capacity of electric vehicles puts constraints on their driving range and requires charging in the process of completing driving tasks. In this paper, with the current practical application in logistics industry as the background, from electric vehicle charging scheduling and path planning, a hybrid algorithm combining genetic-particle swarm algorithm is proposed to plan the best driving route for a group of electric logistics vehicles with vehicle load, vehicle battery life, charging facility location and customer time window as constraints and the total cost as the objective function. Based on the single distribution center, a more complex multi-distribution center electric vehicle path planning problem is considered. In this paper, multiple sets of Solomon VRPTW data sets are selected to test the prepared algorithm, and the results show that the algorithm can effectively plan the best distribution scheme.
基于GA-PSO算法的物流纯电动汽车路径选择
摘要:基于当前电池和燃料电池等储能技术,电动汽车固有的电池容量限制了其续航里程,并需要在完成驾驶任务的过程中充电。本文以当前物流行业的实际应用为背景,从电动汽车充电调度和路径规划两个方面,提出了一种结合遗传粒子群算法的混合算法,以规划一组电动物流车在车辆负载、车辆电池寿命、,以充电设施位置和客户时间窗口为约束条件,以总成本为目标函数。在单个配送中心的基础上,考虑了一个更复杂的多配送中心电动汽车路径规划问题。本文选取了多组Solomon VRPTW数据集对所编制的算法进行了测试,结果表明该算法能够有效地规划最佳分配方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Mechanika
Mechanika 物理-力学
CiteScore
1.30
自引率
0.00%
发文量
50
审稿时长
3 months
期刊介绍: The journal is publishing scientific papers dealing with the following problems: Mechanics of Solid Bodies; Mechanics of Fluids and Gases; Dynamics of Mechanical Systems; Design and Optimization of Mechanical Systems; Mechanical Technologies.
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