{"title":"Linear time algorithm for the vertex-edge domination problem in convex bipartite graphs","authors":"Yasemin Büyükçolak","doi":"10.1016/j.disopt.2024.100877","DOIUrl":null,"url":null,"abstract":"<div><div>Given a graph <span><math><mrow><mi>G</mi><mo>=</mo><mrow><mo>(</mo><mi>V</mi><mo>,</mo><mi>E</mi><mo>)</mo></mrow></mrow></math></span>, a vertex <span><math><mrow><mi>u</mi><mo>∈</mo><mi>V</mi></mrow></math></span> <em>ve-dominates</em> all edges incident to any vertex in the closed neighborhood <span><math><mrow><mi>N</mi><mrow><mo>[</mo><mi>u</mi><mo>]</mo></mrow></mrow></math></span>. A subset <span><math><mrow><mi>D</mi><mo>⊆</mo><mi>V</mi></mrow></math></span> is <em>a vertex-edge dominating set</em> if, for each edge <span><math><mrow><mi>e</mi><mo>∈</mo><mi>E</mi></mrow></math></span>, there exists a vertex <span><math><mrow><mi>u</mi><mo>∈</mo><mi>D</mi></mrow></math></span> such that <span><math><mi>u</mi></math></span> ve-dominates <span><math><mi>e</mi></math></span>. The objective of the <em>ve-domination problem</em> is to find a minimum cardinality ve-dominating set in <span><math><mi>G</mi></math></span>. In this paper, we present a linear time algorithm to find a minimum cardinality ve-dominating set for convex bipartite graphs, which is a superclass of bipartite permutation graphs and a subclass of bipartite graphs, where the ve-domination problem is solvable in linear time and NP-complete, respectively. We also establish the relationship <span><math><mrow><msub><mrow><mi>γ</mi></mrow><mrow><mi>v</mi><mi>e</mi></mrow></msub><mo>=</mo><msub><mrow><mi>i</mi></mrow><mrow><mi>v</mi><mi>e</mi></mrow></msub></mrow></math></span> for convex bipartite graphs. Our approach leverages a chain decomposition of convex bipartite graphs, allowing for efficient identification of minimum ve-dominating sets and extending algorithmic insights into ve-domination for specific structured graph classes.</div></div>","PeriodicalId":50571,"journal":{"name":"Discrete Optimization","volume":"55 ","pages":"Article 100877"},"PeriodicalIF":0.9000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Discrete Optimization","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1572528624000562","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
引用次数: 0
Abstract
Given a graph , a vertex ve-dominates all edges incident to any vertex in the closed neighborhood . A subset is a vertex-edge dominating set if, for each edge , there exists a vertex such that ve-dominates . The objective of the ve-domination problem is to find a minimum cardinality ve-dominating set in . In this paper, we present a linear time algorithm to find a minimum cardinality ve-dominating set for convex bipartite graphs, which is a superclass of bipartite permutation graphs and a subclass of bipartite graphs, where the ve-domination problem is solvable in linear time and NP-complete, respectively. We also establish the relationship for convex bipartite graphs. Our approach leverages a chain decomposition of convex bipartite graphs, allowing for efficient identification of minimum ve-dominating sets and extending algorithmic insights into ve-domination for specific structured graph classes.
期刊介绍:
Discrete Optimization publishes research papers on the mathematical, computational and applied aspects of all areas of integer programming and combinatorial optimization. In addition to reports on mathematical results pertinent to discrete optimization, the journal welcomes submissions on algorithmic developments, computational experiments, and novel applications (in particular, large-scale and real-time applications). The journal also publishes clearly labelled surveys, reviews, short notes, and open problems. Manuscripts submitted for possible publication to Discrete Optimization should report on original research, should not have been previously published, and should not be under consideration for publication by any other journal.