{"title":"b-匹配、Matroid 和 Matchoid 约束条件下的次模态函数最大化半流算法","authors":"Chien-Chung Huang, François Sellier","doi":"10.1007/s00453-024-01272-x","DOIUrl":null,"url":null,"abstract":"<div><p>We consider the problem of maximizing a non-negative submodular function under the <i>b</i>-matching constraint, in the semi-streaming model. When the function is linear, monotone, and non-monotone, we obtain the approximation ratios of <span>\\(2+\\varepsilon \\)</span>, <span>\\(3 + 2 \\sqrt{2} \\approx 5.828\\)</span>, and <span>\\(4 + 2 \\sqrt{3} \\approx 7.464\\)</span>, respectively. We also consider a generalized problem, where a <i>k</i>-uniform hypergraph is given, along with an extra matroid or a <span>\\(k'\\)</span>-matchoid constraint imposed on the edges, with the same goal of finding a <i>b</i>-matching that maximizes a submodular function. When the extra constraint is a matroid, we obtain the approximation ratios of <span>\\(k + 1 + \\varepsilon \\)</span>, <span>\\(k + 2\\sqrt{k+1} + 2\\)</span>, and <span>\\(k + 2\\sqrt{k + 2} + 3\\)</span> for linear, monotone and non-monotone submodular functions, respectively. When the extra constraint is a <span>\\(k'\\)</span>-matchoid, we attain the approximation ratio <span>\\(\\frac{8}{3}k+ \\frac{64}{9}k' + O(1)\\)</span> for general submodular functions.\n</p></div>","PeriodicalId":50824,"journal":{"name":"Algorithmica","volume":"86 11","pages":"3598 - 3628"},"PeriodicalIF":0.9000,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Semi-streaming Algorithms for Submodular Function Maximization Under b-Matching, Matroid, and Matchoid Constraints\",\"authors\":\"Chien-Chung Huang, François Sellier\",\"doi\":\"10.1007/s00453-024-01272-x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>We consider the problem of maximizing a non-negative submodular function under the <i>b</i>-matching constraint, in the semi-streaming model. When the function is linear, monotone, and non-monotone, we obtain the approximation ratios of <span>\\\\(2+\\\\varepsilon \\\\)</span>, <span>\\\\(3 + 2 \\\\sqrt{2} \\\\approx 5.828\\\\)</span>, and <span>\\\\(4 + 2 \\\\sqrt{3} \\\\approx 7.464\\\\)</span>, respectively. We also consider a generalized problem, where a <i>k</i>-uniform hypergraph is given, along with an extra matroid or a <span>\\\\(k'\\\\)</span>-matchoid constraint imposed on the edges, with the same goal of finding a <i>b</i>-matching that maximizes a submodular function. When the extra constraint is a matroid, we obtain the approximation ratios of <span>\\\\(k + 1 + \\\\varepsilon \\\\)</span>, <span>\\\\(k + 2\\\\sqrt{k+1} + 2\\\\)</span>, and <span>\\\\(k + 2\\\\sqrt{k + 2} + 3\\\\)</span> for linear, monotone and non-monotone submodular functions, respectively. When the extra constraint is a <span>\\\\(k'\\\\)</span>-matchoid, we attain the approximation ratio <span>\\\\(\\\\frac{8}{3}k+ \\\\frac{64}{9}k' + O(1)\\\\)</span> for general submodular functions.\\n</p></div>\",\"PeriodicalId\":50824,\"journal\":{\"name\":\"Algorithmica\",\"volume\":\"86 11\",\"pages\":\"3598 - 3628\"},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2024-09-14\",\"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/s00453-024-01272-x\",\"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}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Algorithmica","FirstCategoryId":"94","ListUrlMain":"https://link.springer.com/article/10.1007/s00453-024-01272-x","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}
Semi-streaming Algorithms for Submodular Function Maximization Under b-Matching, Matroid, and Matchoid Constraints
We consider the problem of maximizing a non-negative submodular function under the b-matching constraint, in the semi-streaming model. When the function is linear, monotone, and non-monotone, we obtain the approximation ratios of \(2+\varepsilon \), \(3 + 2 \sqrt{2} \approx 5.828\), and \(4 + 2 \sqrt{3} \approx 7.464\), respectively. We also consider a generalized problem, where a k-uniform hypergraph is given, along with an extra matroid or a \(k'\)-matchoid constraint imposed on the edges, with the same goal of finding a b-matching that maximizes a submodular function. When the extra constraint is a matroid, we obtain the approximation ratios of \(k + 1 + \varepsilon \), \(k + 2\sqrt{k+1} + 2\), and \(k + 2\sqrt{k + 2} + 3\) for linear, monotone and non-monotone submodular functions, respectively. When the extra constraint is a \(k'\)-matchoid, we attain the approximation ratio \(\frac{8}{3}k+ \frac{64}{9}k' + O(1)\) for general submodular functions.
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.