A Hybrid Max-Min Ant System Algorithm for Electric Capacitated Vehicle Routing Problem

被引：0

作者：

Hou, Yan-e ^{[1
]}

Wang, Congran ^{[2
]}

Zhang, Chunyang ^{[3
]}

Dang, Lanxue ^{[4
]}

Xiao, Chunjing ^{[5
]}

机构：

[1] Henan Key Laboratory of Big Data Analysis and Processing, Henan University, Kaifeng,475004, China

[2] College of Computer and Information Engineering, Henan University, Kaifeng,475004, China

[3] College of Computer and Information Engineering, Henan University, Kaifeng,475004, China

[4] College of Computer and Information Engineering, Henan University, Kaifeng,475004, China

[5] School of Computer and Information Engineering, Henan University, Kaifeng,475004, China

来源：

IAENG International Journal of Computer Science | 2024年 / 51卷 / 03期

关键词：

Electric vehicles have become the first choice for products delivery in logistics; due to their environmental friendliness and low cost compared to the traditional fuel vehicles. This paper deals with an electric capacitated vehicle routing problem with variable energy consumption rate (E-CVRP); which aims to minimize the total cost including vehicle fixed cost; traveled distance cost and energy cost. First; a mixed integer linear programming model is constructed based on the fact that the energy consumption is affected by the vehicle load. Second; a hybrid Max-Min Ant System (HMMAS) algorithm is proposed to solve this problem. Three neighborhood structures are introduced and executed in a Variable Neighborhood Descent (VND) algorithm to improve the current solution. In addition; an effective charging station adjustment strategy is adopted to further improve the solution obtained by the local search process. Finally; some experiments have been conducted on public instances; and the results demonstrate the effectiveness and stability of the algorithm. © (2024); (International Association of Engineers). All Rights Reserved;

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摘要：

引用

页码：195 / 203

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