George B. Mertzios , Hendrik Molter , Rolf Niedermeier , Viktor Zamaraev , Philipp Zschoche
{"title":"计算时间图中的最大匹配","authors":"George B. Mertzios , Hendrik Molter , Rolf Niedermeier , Viktor Zamaraev , Philipp Zschoche","doi":"10.1016/j.jcss.2023.04.005","DOIUrl":null,"url":null,"abstract":"<div><p><span>Temporal graphs are graphs whose topology is subject to discrete changes over time. Given a static underlying graph </span><em>G</em>, a temporal graph is represented by assigning a set of integer time-labels to every edge <em>e</em> of <em>G</em><span>, indicating the discrete time steps at which </span><em>e</em><span><span> is active. We introduce and study the complexity of a natural temporal extension of the </span>classical graph problem </span><span>Maximum Matching</span>, taking into account the dynamic nature of temporal graphs. In our problem, <span>Maximum Temporal Matching</span>, we are looking for the largest possible number of time-labeled edges (simply <em>time-edges</em>) <span><math><mo>(</mo><mi>e</mi><mo>,</mo><mi>t</mi><mo>)</mo></math></span> such that no vertex is matched more than once within any time window of Δ consecutive time slots, where <span><math><mi>Δ</mi><mo>∈</mo><mi>N</mi></math></span> is given. We prove strong computational hardness results for <span>Maximum Temporal Matching</span><span>, even for elementary cases, as well as fixed-parameter algorithms with respect to natural parameters and polynomial-time approximation algorithms.</span></p></div>","PeriodicalId":50224,"journal":{"name":"Journal of Computer and System Sciences","volume":"137 ","pages":"Pages 1-19"},"PeriodicalIF":1.1000,"publicationDate":"2023-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Computing maximum matchings in temporal graphs\",\"authors\":\"George B. Mertzios , Hendrik Molter , Rolf Niedermeier , Viktor Zamaraev , Philipp Zschoche\",\"doi\":\"10.1016/j.jcss.2023.04.005\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p><span>Temporal graphs are graphs whose topology is subject to discrete changes over time. Given a static underlying graph </span><em>G</em>, a temporal graph is represented by assigning a set of integer time-labels to every edge <em>e</em> of <em>G</em><span>, indicating the discrete time steps at which </span><em>e</em><span><span> is active. We introduce and study the complexity of a natural temporal extension of the </span>classical graph problem </span><span>Maximum Matching</span>, taking into account the dynamic nature of temporal graphs. In our problem, <span>Maximum Temporal Matching</span>, we are looking for the largest possible number of time-labeled edges (simply <em>time-edges</em>) <span><math><mo>(</mo><mi>e</mi><mo>,</mo><mi>t</mi><mo>)</mo></math></span> such that no vertex is matched more than once within any time window of Δ consecutive time slots, where <span><math><mi>Δ</mi><mo>∈</mo><mi>N</mi></math></span> is given. We prove strong computational hardness results for <span>Maximum Temporal Matching</span><span>, even for elementary cases, as well as fixed-parameter algorithms with respect to natural parameters and polynomial-time approximation algorithms.</span></p></div>\",\"PeriodicalId\":50224,\"journal\":{\"name\":\"Journal of Computer and System Sciences\",\"volume\":\"137 \",\"pages\":\"Pages 1-19\"},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2023-05-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Computer and System Sciences\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0022000023000466\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computer and System Sciences","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0022000023000466","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
Temporal graphs are graphs whose topology is subject to discrete changes over time. Given a static underlying graph G, a temporal graph is represented by assigning a set of integer time-labels to every edge e of G, indicating the discrete time steps at which e is active. We introduce and study the complexity of a natural temporal extension of the classical graph problem Maximum Matching, taking into account the dynamic nature of temporal graphs. In our problem, Maximum Temporal Matching, we are looking for the largest possible number of time-labeled edges (simply time-edges) such that no vertex is matched more than once within any time window of Δ consecutive time slots, where is given. We prove strong computational hardness results for Maximum Temporal Matching, even for elementary cases, as well as fixed-parameter algorithms with respect to natural parameters and polynomial-time approximation algorithms.
期刊介绍:
The Journal of Computer and System Sciences publishes original research papers in computer science and related subjects in system science, with attention to the relevant mathematical theory. Applications-oriented papers may also be accepted and they are expected to contain deep analytic evaluation of the proposed solutions.
Research areas include traditional subjects such as:
• Theory of algorithms and computability
• Formal languages
• Automata theory
Contemporary subjects such as:
• Complexity theory
• Algorithmic Complexity
• Parallel & distributed computing
• Computer networks
• Neural networks
• Computational learning theory
• Database theory & practice
• Computer modeling of complex systems
• Security and Privacy.