{"title":"Connectivity with Uncertainty Regions Given as Line Segments","authors":"Sergio Cabello, David Gajser","doi":"10.1007/s00453-023-01200-5","DOIUrl":null,"url":null,"abstract":"<div><p>For a set <span>\\({\\mathcal {Q}}\\)</span> of points in the plane and a real number <span>\\(\\delta \\ge 0\\)</span>, let <span>\\({\\mathbb {G}}_\\delta ({\\mathcal {Q}})\\)</span> be the graph defined on <span>\\({\\mathcal {Q}}\\)</span> by connecting each pair of points at distance at most <span>\\(\\delta \\)</span>.We consider the connectivity of <span>\\({\\mathbb {G}}_\\delta ({\\mathcal {Q}})\\)</span> in the best scenario when the location of a few of the points is uncertain, but we know for each uncertain point a line segment that contains it. More precisely, we consider the following optimization problem: given a set <span>\\({\\mathcal {P}}\\)</span> of <span>\\(n-k\\)</span> points in the plane and a set <span>\\({\\mathcal {S}}\\)</span> of <i>k</i> line segments in the plane, find the minimum <span>\\(\\delta \\ge 0\\)</span> with the property that we can select one point <span>\\(p_s\\in s\\)</span> for each segment <span>\\(s\\in {\\mathcal {S}}\\)</span> and the corresponding graph <span>\\({\\mathbb {G}}_\\delta ( {\\mathcal {P}}\\cup \\{ p_s\\mid s\\in {\\mathcal {S}}\\})\\)</span> is connected. It is known that the problem is NP-hard. We provide an algorithm to exactly compute an optimal solution in <span>\\({{\\,\\mathrm{{\\mathcal {O}}}\\,}}(f(k) n \\log n)\\)</span> time, for a computable function <span>\\(f(\\cdot )\\)</span>. This implies that the problem is FPT when parameterized by <i>k</i>. The best previous algorithm uses <span>\\({{\\,\\mathrm{{\\mathcal {O}}}\\,}}((k!)^k k^{k+1}\\cdot n^{2k})\\)</span> time and computes the solution up to fixed precision.\n</p></div>","PeriodicalId":50824,"journal":{"name":"Algorithmica","volume":"86 5","pages":"1512 - 1544"},"PeriodicalIF":0.9000,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s00453-023-01200-5.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Algorithmica","FirstCategoryId":"94","ListUrlMain":"https://link.springer.com/article/10.1007/s00453-023-01200-5","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
引用次数: 0
Abstract
For a set \({\mathcal {Q}}\) of points in the plane and a real number \(\delta \ge 0\), let \({\mathbb {G}}_\delta ({\mathcal {Q}})\) be the graph defined on \({\mathcal {Q}}\) by connecting each pair of points at distance at most \(\delta \).We consider the connectivity of \({\mathbb {G}}_\delta ({\mathcal {Q}})\) in the best scenario when the location of a few of the points is uncertain, but we know for each uncertain point a line segment that contains it. More precisely, we consider the following optimization problem: given a set \({\mathcal {P}}\) of \(n-k\) points in the plane and a set \({\mathcal {S}}\) of k line segments in the plane, find the minimum \(\delta \ge 0\) with the property that we can select one point \(p_s\in s\) for each segment \(s\in {\mathcal {S}}\) and the corresponding graph \({\mathbb {G}}_\delta ( {\mathcal {P}}\cup \{ p_s\mid s\in {\mathcal {S}}\})\) is connected. It is known that the problem is NP-hard. We provide an algorithm to exactly compute an optimal solution in \({{\,\mathrm{{\mathcal {O}}}\,}}(f(k) n \log n)\) time, for a computable function \(f(\cdot )\). This implies that the problem is FPT when parameterized by k. The best previous algorithm uses \({{\,\mathrm{{\mathcal {O}}}\,}}((k!)^k k^{k+1}\cdot n^{2k})\) time and computes the solution up to fixed precision.
期刊介绍:
Algorithmica is an international journal which publishes theoretical papers on algorithms that address problems arising in practical areas, and experimental papers of general appeal for practical importance or techniques. The development of algorithms is an integral part of computer science. The increasing complexity and scope of computer applications makes the design of efficient algorithms essential.
Algorithmica covers algorithms in applied areas such as: VLSI, distributed computing, parallel processing, automated design, robotics, graphics, data base design, software tools, as well as algorithms in fundamental areas such as sorting, searching, data structures, computational geometry, and linear programming.
In addition, the journal features two special sections: Application Experience, presenting findings obtained from applications of theoretical results to practical situations, and Problems, offering short papers presenting problems on selected topics of computer science.