Shawn Skyler, Dor Atzmon, Ariel Felner, Oren Salzman, Han Zhang, Sven Koenig, W. Yeoh, Carlos Hernández Ulloa
{"title":"Bounded-Cost Bi-Objective Heuristic Search","authors":"Shawn Skyler, Dor Atzmon, Ariel Felner, Oren Salzman, Han Zhang, Sven Koenig, W. Yeoh, Carlos Hernández Ulloa","doi":"10.1609/socs.v15i1.21774","DOIUrl":null,"url":null,"abstract":"There are many settings that extend the basic shortest path search problem. In Bounded-Cost Search, we are given a constant bound and the task is to find a solution within the bound. In Bi-Objective Search, each edge is associated with two costs (objectives) and the task is to minimize both objectives. In this paper, we combine both these settings into a new setting of Bounded-Cost Bi-Objective Search. We are given two bounds, one for each objective and the task is to find a solution within these bounds. We provide a scheme for normalizing the two objectives. We then introduce several algorithms for this new setting and compare them experimentally.","PeriodicalId":425645,"journal":{"name":"Symposium on Combinatorial Search","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Symposium on Combinatorial Search","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1609/socs.v15i1.21774","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
There are many settings that extend the basic shortest path search problem. In Bounded-Cost Search, we are given a constant bound and the task is to find a solution within the bound. In Bi-Objective Search, each edge is associated with two costs (objectives) and the task is to minimize both objectives. In this paper, we combine both these settings into a new setting of Bounded-Cost Bi-Objective Search. We are given two bounds, one for each objective and the task is to find a solution within these bounds. We provide a scheme for normalizing the two objectives. We then introduce several algorithms for this new setting and compare them experimentally.