{"title":"断开连接带来健壮性?顶点截断匹配的网络设计","authors":"Eugene T.Y. Ang , Yifan Feng","doi":"10.1016/j.orl.2025.107352","DOIUrl":null,"url":null,"abstract":"<div><div>This paper investigates sparse network designs that support large matchings under adversarial vertex deletions. We find that while connected structures (e.g., <em>chain-type</em> graphs) can be optimal when sparsity constraints are less stringent, disconnected structures (e.g., <em>cluster-type</em> graphs) can be optimal otherwise. We characterize the performance of chains and clusters to understand how the preferred design transitions from the former to the latter. Our analysis suggests that clusters are more robust to disruption, making them more advantageous in high-stress environments.</div></div>","PeriodicalId":54682,"journal":{"name":"Operations Research Letters","volume":"63 ","pages":"Article 107352"},"PeriodicalIF":0.9000,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Disconnectedness Brings Robustness? On Network Design For Matching With Vertex Interdiction\",\"authors\":\"Eugene T.Y. Ang , Yifan Feng\",\"doi\":\"10.1016/j.orl.2025.107352\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This paper investigates sparse network designs that support large matchings under adversarial vertex deletions. We find that while connected structures (e.g., <em>chain-type</em> graphs) can be optimal when sparsity constraints are less stringent, disconnected structures (e.g., <em>cluster-type</em> graphs) can be optimal otherwise. We characterize the performance of chains and clusters to understand how the preferred design transitions from the former to the latter. Our analysis suggests that clusters are more robust to disruption, making them more advantageous in high-stress environments.</div></div>\",\"PeriodicalId\":54682,\"journal\":{\"name\":\"Operations Research Letters\",\"volume\":\"63 \",\"pages\":\"Article 107352\"},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2025-08-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Operations Research Letters\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0167637725001130\",\"RegionNum\":4,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"OPERATIONS RESEARCH & MANAGEMENT SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Operations Research Letters","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167637725001130","RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"OPERATIONS RESEARCH & MANAGEMENT SCIENCE","Score":null,"Total":0}
Disconnectedness Brings Robustness? On Network Design For Matching With Vertex Interdiction
This paper investigates sparse network designs that support large matchings under adversarial vertex deletions. We find that while connected structures (e.g., chain-type graphs) can be optimal when sparsity constraints are less stringent, disconnected structures (e.g., cluster-type graphs) can be optimal otherwise. We characterize the performance of chains and clusters to understand how the preferred design transitions from the former to the latter. Our analysis suggests that clusters are more robust to disruption, making them more advantageous in high-stress environments.
期刊介绍:
Operations Research Letters is committed to the rapid review and fast publication of short articles on all aspects of operations research and analytics. Apart from a limitation to eight journal pages, quality, originality, relevance and clarity are the only criteria for selecting the papers to be published. ORL covers the broad field of optimization, stochastic models and game theory. Specific areas of interest include networks, routing, location, queueing, scheduling, inventory, reliability, and financial engineering. We wish to explore interfaces with other fields such as life sciences and health care, artificial intelligence and machine learning, energy distribution, and computational social sciences and humanities. Our traditional strength is in methodology, including theory, modelling, algorithms and computational studies. We also welcome novel applications and concise literature reviews.