A new primal-dual path-following interior-point algorithm for linearly constrained convex optimization

作     者：张敏 白延琴 王国强 ZHANG Min;BAI Yanqin;WANG Guoqiang

作者机构：Department of Mathematics College of Sciences Shanghai University College of Vocational Technology Shanghai University of Engineering Science 

出 版 物：《Journal of Shanghai University(English Edition)》 (上海大学学报（英文版）)

年 卷 期：2008年第12卷第6期

页      面：475-480页

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 07[理学] 070105[理学-运筹学与控制论] 0701[理学-数学] 

基　　金：supported by the Shanghai Pujiang Program (Grant No.06PJ14039) the Science Foundation of Shanghai Municipal Commission of Education (Grant No.06NS031) 

主　　题：linearly constrained convex optimization （LCCO） interior-point algorithm small-update method polynomial complexity 

摘      要：In this paper, a primal-dual path-following interior-point algorithm for linearly constrained convex optimization(LCCO) is *** algorithm is based on a new technique for finding a class of search directions and the strategy of the central *** each iteration, only full-Newton steps are ***, the favorable polynomial complexity bound for the algorithm with the small-update method is deserved, namely, O(√n log n /ε).