{"title":"Maximum Matchings and Popularity","authors":"Telikepalli Kavitha","doi":"10.1137/22m1523248","DOIUrl":null,"url":null,"abstract":"SIAM Journal on Discrete Mathematics, Volume 38, Issue 2, Page 1202-1221, June 2024. <br/> Abstract. Let [math] be a bipartite graph where every node has a strict ranking of its neighbors. For any node, its preferences over neighbors extend naturally to preferences over matchings. A maximum matching [math] in [math] is a popular max-matching if there is no maximum matching more popular than [math]. In other words, for any maximum matching [math], the number of nodes that prefer [math] to [math] is at least the number of nodes that prefer [math] to [math]. It is known that popular max-matchings always exist in [math] and one such matching can be efficiently computed. In this paper we are in the weighted setting, i.e., there is a cost function [math], and our goal is to find a min-cost popular max-matching. We prove that such a matching can be computed in polynomial time by showing a compact extended formulation for the popular max-matching polytope. By contrast, it is known that the popular matching polytope has near-exponential extension complexity and finding a min-cost popular matching is NP-hard. We also consider Pareto-optimality. Though it is easy to find a Pareto-optimal matching/max-matching, we show that it is NP-hard to find a min-cost Pareto-optimal matching/max-matching.","PeriodicalId":49530,"journal":{"name":"SIAM Journal on Discrete Mathematics","volume":"39 1","pages":""},"PeriodicalIF":0.9000,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SIAM Journal on Discrete Mathematics","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1137/22m1523248","RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATHEMATICS","Score":null,"Total":0}
引用次数: 0
Abstract
SIAM Journal on Discrete Mathematics, Volume 38, Issue 2, Page 1202-1221, June 2024. Abstract. Let [math] be a bipartite graph where every node has a strict ranking of its neighbors. For any node, its preferences over neighbors extend naturally to preferences over matchings. A maximum matching [math] in [math] is a popular max-matching if there is no maximum matching more popular than [math]. In other words, for any maximum matching [math], the number of nodes that prefer [math] to [math] is at least the number of nodes that prefer [math] to [math]. It is known that popular max-matchings always exist in [math] and one such matching can be efficiently computed. In this paper we are in the weighted setting, i.e., there is a cost function [math], and our goal is to find a min-cost popular max-matching. We prove that such a matching can be computed in polynomial time by showing a compact extended formulation for the popular max-matching polytope. By contrast, it is known that the popular matching polytope has near-exponential extension complexity and finding a min-cost popular matching is NP-hard. We also consider Pareto-optimality. Though it is easy to find a Pareto-optimal matching/max-matching, we show that it is NP-hard to find a min-cost Pareto-optimal matching/max-matching.
期刊介绍:
SIAM Journal on Discrete Mathematics (SIDMA) publishes research papers of exceptional quality in pure and applied discrete mathematics, broadly interpreted. The journal''s focus is primarily theoretical rather than empirical, but the editors welcome papers that evolve from or have potential application to real-world problems. Submissions must be clearly written and make a significant contribution.
Topics include but are not limited to:
properties of and extremal problems for discrete structures
combinatorial optimization, including approximation algorithms
algebraic and enumerative combinatorics
coding and information theory
additive, analytic combinatorics and number theory
combinatorial matrix theory and spectral graph theory
design and analysis of algorithms for discrete structures
discrete problems in computational complexity
discrete and computational geometry
discrete methods in computational biology, and bioinformatics
probabilistic methods and randomized algorithms.