Qingying He , Wei Liu , Tian-Liang Liu , Qiong Tian
{"title":"航行时间不确定的海上监控无人机和无人水面飞行器鲁棒协调路径规划","authors":"Qingying He , Wei Liu , Tian-Liang Liu , Qiong Tian","doi":"10.1016/j.trb.2025.103284","DOIUrl":null,"url":null,"abstract":"<div><div>This study examines the routing and scheduling of an integrated system of unmanned aerial vehicles (UAVs) and unmanned surface vehicles (USVs) for maritime surveillance. The uncertainties in air and maritime conditions can cause delays in the movements of UAVs and USVs. We introduce a robust coordinated path planning approach for the UAV-USV system, optimizing operational efficiency while accounting for UAV/USV travel time unreliability. Specifically, we propose a novel robust compact formulation for the coordinated path planning problem using the budgeted uncertainty sets. To solve this complex problem, we decompose it into a master problem, i.e., a set partitioning problem, and a subproblem that deals with the robust resource-constrained elementary shortest paths. Furthermore, we propose a customized branch-and-price-and-cut solution algorithm to efficiently solve the robust path planning problem. Numerical studies illustrate that our approach can produce solutions that are significantly more robust than those that ignore uncertainty.</div></div>","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"199 ","pages":"Article 103284"},"PeriodicalIF":6.3000,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Robust coordinated path planning for unmanned aerial vehicles and unmanned surface vehicles in maritime monitoring with travel time uncertainty\",\"authors\":\"Qingying He , Wei Liu , Tian-Liang Liu , Qiong Tian\",\"doi\":\"10.1016/j.trb.2025.103284\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This study examines the routing and scheduling of an integrated system of unmanned aerial vehicles (UAVs) and unmanned surface vehicles (USVs) for maritime surveillance. The uncertainties in air and maritime conditions can cause delays in the movements of UAVs and USVs. We introduce a robust coordinated path planning approach for the UAV-USV system, optimizing operational efficiency while accounting for UAV/USV travel time unreliability. Specifically, we propose a novel robust compact formulation for the coordinated path planning problem using the budgeted uncertainty sets. To solve this complex problem, we decompose it into a master problem, i.e., a set partitioning problem, and a subproblem that deals with the robust resource-constrained elementary shortest paths. Furthermore, we propose a customized branch-and-price-and-cut solution algorithm to efficiently solve the robust path planning problem. Numerical studies illustrate that our approach can produce solutions that are significantly more robust than those that ignore uncertainty.</div></div>\",\"PeriodicalId\":54418,\"journal\":{\"name\":\"Transportation Research Part B-Methodological\",\"volume\":\"199 \",\"pages\":\"Article 103284\"},\"PeriodicalIF\":6.3000,\"publicationDate\":\"2025-07-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transportation Research Part B-Methodological\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S019126152500133X\",\"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 B-Methodological","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S019126152500133X","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
Robust coordinated path planning for unmanned aerial vehicles and unmanned surface vehicles in maritime monitoring with travel time uncertainty
This study examines the routing and scheduling of an integrated system of unmanned aerial vehicles (UAVs) and unmanned surface vehicles (USVs) for maritime surveillance. The uncertainties in air and maritime conditions can cause delays in the movements of UAVs and USVs. We introduce a robust coordinated path planning approach for the UAV-USV system, optimizing operational efficiency while accounting for UAV/USV travel time unreliability. Specifically, we propose a novel robust compact formulation for the coordinated path planning problem using the budgeted uncertainty sets. To solve this complex problem, we decompose it into a master problem, i.e., a set partitioning problem, and a subproblem that deals with the robust resource-constrained elementary shortest paths. Furthermore, we propose a customized branch-and-price-and-cut solution algorithm to efficiently solve the robust path planning problem. Numerical studies illustrate that our approach can produce solutions that are significantly more robust than those that ignore uncertainty.
期刊介绍:
Transportation Research: Part B publishes papers on all methodological aspects of the subject, particularly those that require mathematical analysis. The general theme of the journal is the development and solution of problems that are adequately motivated to deal with important aspects of the design and/or analysis of transportation systems. Areas covered include: traffic flow; design and analysis of transportation networks; control and scheduling; optimization; queuing theory; logistics; supply chains; development and application of statistical, econometric and mathematical models to address transportation problems; cost models; pricing and/or investment; traveler or shipper behavior; cost-benefit methodologies.