{"title":"Research on green vehicle routing problems with mixed fleet","authors":"Changshi Liu, Jianqin Zhou","doi":"10.1117/12.2670305","DOIUrl":null,"url":null,"abstract":"Currently, electric vehicles and fuel vehicles coexist in urban distribution. Given this, this paper focuses on the vehicle routing problem with the mixture of electric and fuel vehicles. Then, a green vehicle routing optimization model with a mixed fleet is proposed. The cost of carbon emissions from the fuel is considered in the model. Then, an improved genetic algorithm is designed to solve the problem. Finally, sensitivity analysis is carried out for key factors such as vehicle composition, battery capacity, and charging rate. Numerical experimental results show that the economic power of logistics enterprises to directly upgrade their fleets from all-fuel vehicles to all-electric vehicles is insufficient. The number of electric vehicles kept in the fleet should be determined according to the combination of vehicle cruising range and customer distribution. Logistics enterprises should comprehensively consider the battery capacity and charging rate to reduce the distribution cost of electric vehicles.","PeriodicalId":143377,"journal":{"name":"International Conference on Green Communication, Network, and Internet of Things","volume":"77 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Green Communication, Network, and Internet of Things","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2670305","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Currently, electric vehicles and fuel vehicles coexist in urban distribution. Given this, this paper focuses on the vehicle routing problem with the mixture of electric and fuel vehicles. Then, a green vehicle routing optimization model with a mixed fleet is proposed. The cost of carbon emissions from the fuel is considered in the model. Then, an improved genetic algorithm is designed to solve the problem. Finally, sensitivity analysis is carried out for key factors such as vehicle composition, battery capacity, and charging rate. Numerical experimental results show that the economic power of logistics enterprises to directly upgrade their fleets from all-fuel vehicles to all-electric vehicles is insufficient. The number of electric vehicles kept in the fleet should be determined according to the combination of vehicle cruising range and customer distribution. Logistics enterprises should comprehensively consider the battery capacity and charging rate to reduce the distribution cost of electric vehicles.