{"title":"优化电动卡车路线的牛奶收集问题:一个真实的案例研究","authors":"Mehmet Erdem","doi":"10.1080/19427867.2022.2044581","DOIUrl":null,"url":null,"abstract":"<div><p>This study dwells upon the electric milk collection problem. The problem extends electric vehicle routing problem with time windows, considering multi-depot, multi-product, split deliveries, multi-compartment, fast chargers and fleet composition. The problem aims to create an effective routing decision-making system for electric trucks in transporting milk of different quality from producers (or milk collection points) in different locations to the factories. The objective of the electric milk collection problem is to minimize the sum of the total energy costs of electric trucks. We develop an adaptive general variable neighborhood search algorithm that involves several procedures having been tailored to handle specific features of the problem. We perform extensive computational experiments on real-life data to investigate the performance of the heuristics and offer particular insight. The results indicate that our algorithm successfully solves small- and large-scale instances in terms of solution quality and computational time. Our results also quantify the benefits of using fast charger types and fleet composition on the total energy costs.</p></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"15 3","pages":"Pages 193-210"},"PeriodicalIF":3.3000,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Optimisation of the electric truck route for milk collection problem: a real case study\",\"authors\":\"Mehmet Erdem\",\"doi\":\"10.1080/19427867.2022.2044581\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This study dwells upon the electric milk collection problem. The problem extends electric vehicle routing problem with time windows, considering multi-depot, multi-product, split deliveries, multi-compartment, fast chargers and fleet composition. The problem aims to create an effective routing decision-making system for electric trucks in transporting milk of different quality from producers (or milk collection points) in different locations to the factories. The objective of the electric milk collection problem is to minimize the sum of the total energy costs of electric trucks. We develop an adaptive general variable neighborhood search algorithm that involves several procedures having been tailored to handle specific features of the problem. We perform extensive computational experiments on real-life data to investigate the performance of the heuristics and offer particular insight. The results indicate that our algorithm successfully solves small- and large-scale instances in terms of solution quality and computational time. Our results also quantify the benefits of using fast charger types and fleet composition on the total energy costs.</p></div>\",\"PeriodicalId\":48974,\"journal\":{\"name\":\"Transportation Letters-The International Journal of Transportation Research\",\"volume\":\"15 3\",\"pages\":\"Pages 193-210\"},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2023-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transportation Letters-The International Journal of Transportation Research\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/org/science/article/pii/S1942786722004751\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"TRANSPORTATION\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Letters-The International Journal of Transportation Research","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/org/science/article/pii/S1942786722004751","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"TRANSPORTATION","Score":null,"Total":0}
Optimisation of the electric truck route for milk collection problem: a real case study
This study dwells upon the electric milk collection problem. The problem extends electric vehicle routing problem with time windows, considering multi-depot, multi-product, split deliveries, multi-compartment, fast chargers and fleet composition. The problem aims to create an effective routing decision-making system for electric trucks in transporting milk of different quality from producers (or milk collection points) in different locations to the factories. The objective of the electric milk collection problem is to minimize the sum of the total energy costs of electric trucks. We develop an adaptive general variable neighborhood search algorithm that involves several procedures having been tailored to handle specific features of the problem. We perform extensive computational experiments on real-life data to investigate the performance of the heuristics and offer particular insight. The results indicate that our algorithm successfully solves small- and large-scale instances in terms of solution quality and computational time. Our results also quantify the benefits of using fast charger types and fleet composition on the total energy costs.
期刊介绍:
Transportation Letters: The International Journal of Transportation Research is a quarterly journal that publishes high-quality peer-reviewed and mini-review papers as well as technical notes and book reviews on the state-of-the-art in transportation research.
The focus of Transportation Letters is on analytical and empirical findings, methodological papers, and theoretical and conceptual insights across all areas of research. Review resource papers that merge descriptions of the state-of-the-art with innovative and new methodological, theoretical, and conceptual insights spanning all areas of transportation research are invited and of particular interest.