{"title":"最小代价单源不可分流问题的新算法","authors":"Chao Peng, Yasuo Tan, L. Yang","doi":"10.1109/AINAW.2007.266","DOIUrl":null,"url":null,"abstract":"The minimum-cost single-source unsplittable flow problem is a single-source multi-commodity flow problem in which each commodity should be shipped only on one single path at the minimum possible cost without violating the capacity of each edge. An outstanding open question on this problem is whether a simultaneous (2,1)-approximation can be achieved for minimizing congestion and cost. But for the general version so far the best possible ratio is (3 + 2radic(2),1). In this paper we present a polynomial-time approximation algorithms which achieves this approximation ratio, our algorithm is more efficient and easier to implement compares to previous algorithms for this problem.","PeriodicalId":338799,"journal":{"name":"21st International Conference on Advanced Information Networking and Applications Workshops (AINAW'07)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"New Algorithms for the Minimum-Cost Single-Source Unsplittable Flow Problem\",\"authors\":\"Chao Peng, Yasuo Tan, L. Yang\",\"doi\":\"10.1109/AINAW.2007.266\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The minimum-cost single-source unsplittable flow problem is a single-source multi-commodity flow problem in which each commodity should be shipped only on one single path at the minimum possible cost without violating the capacity of each edge. An outstanding open question on this problem is whether a simultaneous (2,1)-approximation can be achieved for minimizing congestion and cost. But for the general version so far the best possible ratio is (3 + 2radic(2),1). In this paper we present a polynomial-time approximation algorithms which achieves this approximation ratio, our algorithm is more efficient and easier to implement compares to previous algorithms for this problem.\",\"PeriodicalId\":338799,\"journal\":{\"name\":\"21st International Conference on Advanced Information Networking and Applications Workshops (AINAW'07)\",\"volume\":\"82 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-05-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"21st International Conference on Advanced Information Networking and Applications Workshops (AINAW'07)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AINAW.2007.266\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"21st International Conference on Advanced Information Networking and Applications Workshops (AINAW'07)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AINAW.2007.266","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
New Algorithms for the Minimum-Cost Single-Source Unsplittable Flow Problem
The minimum-cost single-source unsplittable flow problem is a single-source multi-commodity flow problem in which each commodity should be shipped only on one single path at the minimum possible cost without violating the capacity of each edge. An outstanding open question on this problem is whether a simultaneous (2,1)-approximation can be achieved for minimizing congestion and cost. But for the general version so far the best possible ratio is (3 + 2radic(2),1). In this paper we present a polynomial-time approximation algorithms which achieves this approximation ratio, our algorithm is more efficient and easier to implement compares to previous algorithms for this problem.