{"title":"移动和固定充电器协同的电动汽车充电优化","authors":"Xiaofeng Li, Xinlian Yu, Ziyuan Pu, Jingxu Chen","doi":"10.1016/j.tre.2025.104434","DOIUrl":null,"url":null,"abstract":"<div><div>Mobile Chargers (MCs) enhance the flexibility and convenience of Electric Vehicle (EV) charging by enabling spatial–temporal power transfer, yet their effectiveness depends on optimal recharging strategies. This study addresses the EV charging problem using both fixed chargers (FCs) and MCs, considering the recharging of MCs at FC sites. A mixed-integer programming model is developed to integrate the operation of FCs and MCs, taking into account several practical considerations, including the time constraints of EV charging requests, the limited capacity of FCs, and the need to recharge MCs between serving EVs. A two-layer adaptive large neighborhood search algorithm is designed with problem-tailored removal and insertion operators. Computational experiment with instances constructed using real world charging data demonstrate the effectiveness of the proposed algorithm and the tailored operators. Managerial insights into operation efficiency are also provided, especially concerning the battery size of MCs and geographic distributions of FCs.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"204 ","pages":"Article 104434"},"PeriodicalIF":8.8000,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Electric vehicle charging optimization with coordinated mobile and fixed chargers\",\"authors\":\"Xiaofeng Li, Xinlian Yu, Ziyuan Pu, Jingxu Chen\",\"doi\":\"10.1016/j.tre.2025.104434\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Mobile Chargers (MCs) enhance the flexibility and convenience of Electric Vehicle (EV) charging by enabling spatial–temporal power transfer, yet their effectiveness depends on optimal recharging strategies. This study addresses the EV charging problem using both fixed chargers (FCs) and MCs, considering the recharging of MCs at FC sites. A mixed-integer programming model is developed to integrate the operation of FCs and MCs, taking into account several practical considerations, including the time constraints of EV charging requests, the limited capacity of FCs, and the need to recharge MCs between serving EVs. A two-layer adaptive large neighborhood search algorithm is designed with problem-tailored removal and insertion operators. Computational experiment with instances constructed using real world charging data demonstrate the effectiveness of the proposed algorithm and the tailored operators. Managerial insights into operation efficiency are also provided, especially concerning the battery size of MCs and geographic distributions of FCs.</div></div>\",\"PeriodicalId\":49418,\"journal\":{\"name\":\"Transportation Research Part E-Logistics and Transportation Review\",\"volume\":\"204 \",\"pages\":\"Article 104434\"},\"PeriodicalIF\":8.8000,\"publicationDate\":\"2025-09-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transportation Research Part E-Logistics and Transportation Review\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1366554525004752\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research Part E-Logistics and Transportation Review","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1366554525004752","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
Electric vehicle charging optimization with coordinated mobile and fixed chargers
Mobile Chargers (MCs) enhance the flexibility and convenience of Electric Vehicle (EV) charging by enabling spatial–temporal power transfer, yet their effectiveness depends on optimal recharging strategies. This study addresses the EV charging problem using both fixed chargers (FCs) and MCs, considering the recharging of MCs at FC sites. A mixed-integer programming model is developed to integrate the operation of FCs and MCs, taking into account several practical considerations, including the time constraints of EV charging requests, the limited capacity of FCs, and the need to recharge MCs between serving EVs. A two-layer adaptive large neighborhood search algorithm is designed with problem-tailored removal and insertion operators. Computational experiment with instances constructed using real world charging data demonstrate the effectiveness of the proposed algorithm and the tailored operators. Managerial insights into operation efficiency are also provided, especially concerning the battery size of MCs and geographic distributions of FCs.
期刊介绍:
Transportation Research Part E: Logistics and Transportation Review is a reputable journal that publishes high-quality articles covering a wide range of topics in the field of logistics and transportation research. The journal welcomes submissions on various subjects, including transport economics, transport infrastructure and investment appraisal, evaluation of public policies related to transportation, empirical and analytical studies of logistics management practices and performance, logistics and operations models, and logistics and supply chain management.
Part E aims to provide informative and well-researched articles that contribute to the understanding and advancement of the field. The content of the journal is complementary to other prestigious journals in transportation research, such as Transportation Research Part A: Policy and Practice, Part B: Methodological, Part C: Emerging Technologies, Part D: Transport and Environment, and Part F: Traffic Psychology and Behaviour. Together, these journals form a comprehensive and cohesive reference for current research in transportation science.