A new kernel function yielding the best known iteration bounds for primal-dual interior-point algorithms

被引：16
|
作者：
Bai, Yan Qin [1 ]
Guo, Jin Li [2 ]
Roos, Cornelis [3 ]
机构：
[1] Shanghai Univ, Dept Math, Shanghai 200436, Peoples R China
[2] Shanghai Univ Sci & Technol, Sch Business, Shanghai 200093, Peoples R China
[3] Delft Univ Technol, Fac Elect Engn Math & Comp Sci, NL-2600 GA Delft, Netherlands
来源：
ACTA MATHEMATICA SINICA-ENGLISH SERIES | 2009年 / 25卷 / 12期
基金：
中国国家自然科学基金;
关键词：
linear optimization; interior-point method; primal-dual method; large-update method; polynomial complexity;
D O I：
10.1007/s10114-009-6457-8
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
Kernel functions play an important role in defining new search directions for primal-dual interior-point algorithm for solving linear optimization problems. In this paper we present a new kernel function which yields an algorithm with the best known complexity bound for both large- and small-update methods.
引用
收藏
页码：2169 / 2178
页数：10
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