{"title":"用逐次逼近法求解最小成本流问题","authors":"A. Goldberg, R. Tarjan","doi":"10.1145/28395.28397","DOIUrl":null,"url":null,"abstract":"We introduce a framework for solving minimum-cost flow problems. Our approach measures the quality of a solution by the amount that the complementary slackness conditions are violated. We show how to extend techniques developed for the maximum flow problem to improve the quality of a solution. This framework allows us to achieve &Ogr;(min(n3, n5/3 m2/3, nm log n) log (nC)) running time.","PeriodicalId":161795,"journal":{"name":"Proceedings of the nineteenth annual ACM symposium on Theory of computing","volume":"136 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1987-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"255","resultStr":"{\"title\":\"Solving minimum-cost flow problems by successive approximation\",\"authors\":\"A. Goldberg, R. Tarjan\",\"doi\":\"10.1145/28395.28397\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We introduce a framework for solving minimum-cost flow problems. Our approach measures the quality of a solution by the amount that the complementary slackness conditions are violated. We show how to extend techniques developed for the maximum flow problem to improve the quality of a solution. This framework allows us to achieve &Ogr;(min(n3, n5/3 m2/3, nm log n) log (nC)) running time.\",\"PeriodicalId\":161795,\"journal\":{\"name\":\"Proceedings of the nineteenth annual ACM symposium on Theory of computing\",\"volume\":\"136 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1987-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"255\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the nineteenth annual ACM symposium on Theory of computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/28395.28397\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the nineteenth annual ACM symposium on Theory of computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/28395.28397","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Solving minimum-cost flow problems by successive approximation
We introduce a framework for solving minimum-cost flow problems. Our approach measures the quality of a solution by the amount that the complementary slackness conditions are violated. We show how to extend techniques developed for the maximum flow problem to improve the quality of a solution. This framework allows us to achieve &Ogr;(min(n3, n5/3 m2/3, nm log n) log (nC)) running time.
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