{"title":"Approximation Algorithms for Covering Vertices by Long Paths","authors":"Mingyang Gong, Brett Edgar, Jing Fan, Guohui Lin, Eiji Miyano","doi":"10.1007/s00453-024-01242-3","DOIUrl":null,"url":null,"abstract":"<div><p>Given a graph, the general problem to cover the maximum number of vertices by a collection of vertex-disjoint long paths seems to escape from the literature. A path containing at least <i>k</i> vertices is considered long. When <span>\\(k \\le 3\\)</span>, the problem is polynomial time solvable; when <i>k</i> is the total number of vertices, the problem reduces to the Hamiltonian path problem, which is NP-complete. For a fixed <span>\\(k \\ge 4\\)</span>, the problem is NP-hard and the best known approximation algorithm for the weighted set packing problem implies a <i>k</i>-approximation algorithm. To the best of our knowledge, there is no approximation algorithm directly designed for the general problem; when <span>\\(k = 4\\)</span>, the problem admits a 4-approximation algorithm which was presented recently. We propose the first <span>\\((0.4394 k + O(1))\\)</span>-approximation algorithm for the general problem and an improved 2-approximation algorithm when <span>\\(k = 4\\)</span>. Both algorithms are based on local improvement, and their theoretical performance analyses are done via amortization and their practical performance is examined through simulation studies.\n</p></div>","PeriodicalId":50824,"journal":{"name":"Algorithmica","volume":"86 8","pages":"2625 - 2651"},"PeriodicalIF":0.9000,"publicationDate":"2024-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Algorithmica","FirstCategoryId":"94","ListUrlMain":"https://link.springer.com/article/10.1007/s00453-024-01242-3","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
Given a graph, the general problem to cover the maximum number of vertices by a collection of vertex-disjoint long paths seems to escape from the literature. A path containing at least k vertices is considered long. When \(k \le 3\), the problem is polynomial time solvable; when k is the total number of vertices, the problem reduces to the Hamiltonian path problem, which is NP-complete. For a fixed \(k \ge 4\), the problem is NP-hard and the best known approximation algorithm for the weighted set packing problem implies a k-approximation algorithm. To the best of our knowledge, there is no approximation algorithm directly designed for the general problem; when \(k = 4\), the problem admits a 4-approximation algorithm which was presented recently. We propose the first \((0.4394 k + O(1))\)-approximation algorithm for the general problem and an improved 2-approximation algorithm when \(k = 4\). Both algorithms are based on local improvement, and their theoretical performance analyses are done via amortization and their practical performance is examined through simulation studies.
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.