Sayan Bandyapadhyay, Neeraj Kumar, S. Suri, Kasturi R. Varadarajan
{"title":"最小约束去除问题的改进逼近界","authors":"Sayan Bandyapadhyay, Neeraj Kumar, S. Suri, Kasturi R. Varadarajan","doi":"10.4230/LIPIcs.APPROX-RANDOM.2018.2","DOIUrl":null,"url":null,"abstract":"Abstract In the minimum constraint removal problem, we are given a set of overlapping geometric objects as obstacles in the plane, and we want to find the minimum number of obstacles that must be removed to reach a target point t from the source point s by an obstacle-free path. The problem is known to be intractable and no sub-linear approximations are known even for simple obstacles such as rectangles and disks. The main result of our paper is an approximation framework that gives an O ( n α ( n ) ) -approximation for polygonal obstacles, where α ( n ) denotes the inverse Ackermann's function. For pseudodisks and rectilinear polygons, the same technique achieves an O ( n ) -approximation. The technique also gives O ( n ) -approximation for the minimum color path problem in graphs. We also present some inapproximability results for the geometric constraint removal problem.","PeriodicalId":11245,"journal":{"name":"Discret. Comput. Geom.","volume":"29 1","pages":"101650"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Improved Approximation Bounds for the Minimum Constraint Removal Problem\",\"authors\":\"Sayan Bandyapadhyay, Neeraj Kumar, S. Suri, Kasturi R. Varadarajan\",\"doi\":\"10.4230/LIPIcs.APPROX-RANDOM.2018.2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract In the minimum constraint removal problem, we are given a set of overlapping geometric objects as obstacles in the plane, and we want to find the minimum number of obstacles that must be removed to reach a target point t from the source point s by an obstacle-free path. The problem is known to be intractable and no sub-linear approximations are known even for simple obstacles such as rectangles and disks. The main result of our paper is an approximation framework that gives an O ( n α ( n ) ) -approximation for polygonal obstacles, where α ( n ) denotes the inverse Ackermann's function. For pseudodisks and rectilinear polygons, the same technique achieves an O ( n ) -approximation. The technique also gives O ( n ) -approximation for the minimum color path problem in graphs. We also present some inapproximability results for the geometric constraint removal problem.\",\"PeriodicalId\":11245,\"journal\":{\"name\":\"Discret. Comput. Geom.\",\"volume\":\"29 1\",\"pages\":\"101650\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Discret. Comput. Geom.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4230/LIPIcs.APPROX-RANDOM.2018.2\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Discret. Comput. Geom.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4230/LIPIcs.APPROX-RANDOM.2018.2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Improved Approximation Bounds for the Minimum Constraint Removal Problem
Abstract In the minimum constraint removal problem, we are given a set of overlapping geometric objects as obstacles in the plane, and we want to find the minimum number of obstacles that must be removed to reach a target point t from the source point s by an obstacle-free path. The problem is known to be intractable and no sub-linear approximations are known even for simple obstacles such as rectangles and disks. The main result of our paper is an approximation framework that gives an O ( n α ( n ) ) -approximation for polygonal obstacles, where α ( n ) denotes the inverse Ackermann's function. For pseudodisks and rectilinear polygons, the same technique achieves an O ( n ) -approximation. The technique also gives O ( n ) -approximation for the minimum color path problem in graphs. We also present some inapproximability results for the geometric constraint removal problem.