A hybrid genetic algorithm for the electric vehicle routing problem with time windows
Qixing Liu1
Peng Xu1
Yuhu Wu1
Tielong Shen2
1.School of Control Science and Engineering,Dalian University of Technology,Dalian 116024,China2.Department of Mechanical Engineering,Sophia University,Tokyo 102-8554,Japan
摘要：Driven by the new legislation on greenhouse gas emissions,carriers began to use electric vehicles(EVs)for logistics transporta-tion.This paper addresses an electric vehicle routing problem with time windows(EVRPTW).The electricity consumption of EVs is expressed by the battery state-of-charge(SoC).To make it more realistic,we take into account the terrain grades of roads,which affect the travel process of EVs.Within our work,the battery SoC dynamics of EVs are used to describe this situation.We aim to minimize the total electricity consumption while serving a set of customers.To tackle this problem,we formulate the problem as a mixed integer programming model.Furthermore,we develop a hybrid genetic algorithm(GA)that combines the 2-opt algorithm with GA.In simulation results,by the comparison of the simulated annealing(SA)algorithm and GA,the proposed approach indicates that it can provide better solutions in a short time.
机标关键词：windowsalgorithmgeneticroutinghybridelectricwithtime
论文发表日期：2022-01-01
在线出版日期：2025-08-15（本平台首次上网日期，不代表文献的发表时间）
页数：8( 279-286 )
英文信息