{"title":"Planning of truck platooning for road-network capacitated vehicle routing problem","authors":"Yilang Hao, Zhibin Chen, Xiaotong Sun, Lu Tong","doi":"10.1016/j.tre.2024.103898","DOIUrl":null,"url":null,"abstract":"Truck platooning, a linking technology of trucks on the highway, has gained enormous attention in recent years due to its benefits in energy and operation cost savings. However, most existing studies on truck platooning limit their focus on particular scenarios that each truck can serve only one customer demand and is thus with a specified origin–destination pair, so only routing and time schedules are taken into account. Nevertheless, in real-world logistics, each truck may need to serve multiple customers located at different places, and the operator managing a fleet of trucks thus has to determine not only the routing and time schedules of each truck but also the set of customers allocated to each truck and their sequence to visit. This is well known as a capacitated vehicle routing problem with time windows (CVRPTW), and considering the application of truck platooning in such a problem entails new modeling frameworks and tailored solution algorithms. In light of this, this study makes the first attempt to optimize the truck platooning plan for a road-network CVRPTW in a way to minimize the total operation cost, including vehicles’ fixed dispatch cost and energy cost, while fulfilling all delivery demands within their time window constraints. Specifically, the operation plan will dictate the number of trucks to be dispatched, the set of customers, and the routing and time schedules for each truck. In addition, the modeling framework is constructed based on a road network instead of a traditional customer node graph to better resemble and facilitate the platooning operation. A 3-stage algorithm embedded with a ”route-then-schedule” scheme, Dynamic Programming, and Modified Insertion heuristic, is developed to solve the proposed model in a timely manner. Numerical experiments are conducted to validate the proposed modeling framework, demonstrate the performance of the proposed solution algorithm, and quantify the benefit brought by the truck platooning technology.","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"5 1","pages":""},"PeriodicalIF":8.3000,"publicationDate":"2024-12-11","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://doi.org/10.1016/j.tre.2024.103898","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
Truck platooning, a linking technology of trucks on the highway, has gained enormous attention in recent years due to its benefits in energy and operation cost savings. However, most existing studies on truck platooning limit their focus on particular scenarios that each truck can serve only one customer demand and is thus with a specified origin–destination pair, so only routing and time schedules are taken into account. Nevertheless, in real-world logistics, each truck may need to serve multiple customers located at different places, and the operator managing a fleet of trucks thus has to determine not only the routing and time schedules of each truck but also the set of customers allocated to each truck and their sequence to visit. This is well known as a capacitated vehicle routing problem with time windows (CVRPTW), and considering the application of truck platooning in such a problem entails new modeling frameworks and tailored solution algorithms. In light of this, this study makes the first attempt to optimize the truck platooning plan for a road-network CVRPTW in a way to minimize the total operation cost, including vehicles’ fixed dispatch cost and energy cost, while fulfilling all delivery demands within their time window constraints. Specifically, the operation plan will dictate the number of trucks to be dispatched, the set of customers, and the routing and time schedules for each truck. In addition, the modeling framework is constructed based on a road network instead of a traditional customer node graph to better resemble and facilitate the platooning operation. A 3-stage algorithm embedded with a ”route-then-schedule” scheme, Dynamic Programming, and Modified Insertion heuristic, is developed to solve the proposed model in a timely manner. Numerical experiments are conducted to validate the proposed modeling framework, demonstrate the performance of the proposed solution algorithm, and quantify the benefit brought by the truck platooning technology.
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.