{"title":"基于简单核函数的二阶锥规划的内点法","authors":"Li Dong, Jingyong Tang","doi":"10.1109/CINC.2010.5643888","DOIUrl":null,"url":null,"abstract":"Interior-point methods not only are the most effective methods in practice but also have polynomial-time complexity. In this paper we present a primal-dual interiorpoint algorithm for second-order cone programming problems based on a simple kernel function. We derive the iteration bounds O(nlogε/n over n) and O(√nlogε/n over n) for large- and small-update methods, respectively, which are as good as those in the linear programming.","PeriodicalId":227004,"journal":{"name":"2010 Second International Conference on Computational Intelligence and Natural Computing","volume":"103 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Interior-point method for second-order cone programming based on a simple kernel function\",\"authors\":\"Li Dong, Jingyong Tang\",\"doi\":\"10.1109/CINC.2010.5643888\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Interior-point methods not only are the most effective methods in practice but also have polynomial-time complexity. In this paper we present a primal-dual interiorpoint algorithm for second-order cone programming problems based on a simple kernel function. We derive the iteration bounds O(nlogε/n over n) and O(√nlogε/n over n) for large- and small-update methods, respectively, which are as good as those in the linear programming.\",\"PeriodicalId\":227004,\"journal\":{\"name\":\"2010 Second International Conference on Computational Intelligence and Natural Computing\",\"volume\":\"103 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-11-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 Second International Conference on Computational Intelligence and Natural Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CINC.2010.5643888\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Second International Conference on Computational Intelligence and Natural Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CINC.2010.5643888","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Interior-point method for second-order cone programming based on a simple kernel function
Interior-point methods not only are the most effective methods in practice but also have polynomial-time complexity. In this paper we present a primal-dual interiorpoint algorithm for second-order cone programming problems based on a simple kernel function. We derive the iteration bounds O(nlogε/n over n) and O(√nlogε/n over n) for large- and small-update methods, respectively, which are as good as those in the linear programming.
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