Waiming Zhu , Haiquan Sun , Xiaoxuan Hu , Yingying Ma
{"title":"基于储物柜的无人机送货时间跨度最小化问题的可变邻域搜索算法","authors":"Waiming Zhu , Haiquan Sun , Xiaoxuan Hu , Yingying Ma","doi":"10.1016/j.tre.2024.103820","DOIUrl":null,"url":null,"abstract":"<div><div>This article studies a novel makespan minimization problem for locker-based drone delivery in which several automatic drones take lockers as launching and landing platforms. It is a vehicle routing and machine scheduling hybrid problem with formulation and solution challenges. Firstly, we formally define the problem and analyze its complexity. Secondly, we formulate an integer linear program model based on a time-expanded network. Thirdly, we develop a variable neighborhood search algorithm that embeds a translation heuristic. The translation heuristic first constructs a rough solution and then improves the solution by solving a linear program. Numerical tests are conducted on simulated instances. The results show that the algorithm finds solutions with an average gap of 7% for small-scale uniform instances and demonstrates good scalability, with CPU time growing nearly linearly as the instance size increases.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"192 ","pages":"Article 103820"},"PeriodicalIF":8.3000,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A variable neighborhood search algorithm for locker-based drone delivery makespan minimization problem\",\"authors\":\"Waiming Zhu , Haiquan Sun , Xiaoxuan Hu , Yingying Ma\",\"doi\":\"10.1016/j.tre.2024.103820\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This article studies a novel makespan minimization problem for locker-based drone delivery in which several automatic drones take lockers as launching and landing platforms. It is a vehicle routing and machine scheduling hybrid problem with formulation and solution challenges. Firstly, we formally define the problem and analyze its complexity. Secondly, we formulate an integer linear program model based on a time-expanded network. Thirdly, we develop a variable neighborhood search algorithm that embeds a translation heuristic. The translation heuristic first constructs a rough solution and then improves the solution by solving a linear program. Numerical tests are conducted on simulated instances. The results show that the algorithm finds solutions with an average gap of 7% for small-scale uniform instances and demonstrates good scalability, with CPU time growing nearly linearly as the instance size increases.</div></div>\",\"PeriodicalId\":49418,\"journal\":{\"name\":\"Transportation Research Part E-Logistics and Transportation Review\",\"volume\":\"192 \",\"pages\":\"Article 103820\"},\"PeriodicalIF\":8.3000,\"publicationDate\":\"2024-10-18\",\"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/S1366554524004113\",\"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/S1366554524004113","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
A variable neighborhood search algorithm for locker-based drone delivery makespan minimization problem
This article studies a novel makespan minimization problem for locker-based drone delivery in which several automatic drones take lockers as launching and landing platforms. It is a vehicle routing and machine scheduling hybrid problem with formulation and solution challenges. Firstly, we formally define the problem and analyze its complexity. Secondly, we formulate an integer linear program model based on a time-expanded network. Thirdly, we develop a variable neighborhood search algorithm that embeds a translation heuristic. The translation heuristic first constructs a rough solution and then improves the solution by solving a linear program. Numerical tests are conducted on simulated instances. The results show that the algorithm finds solutions with an average gap of 7% for small-scale uniform instances and demonstrates good scalability, with CPU time growing nearly linearly as the instance size increases.
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.