New complexity analysis for primal-dual interior-point methods for self-scaled optimization problems

被引：4

作者：

Choi, Bo Kyung ^{[1
]}

Lee, Gue Myung ^{[1
]}

机构：

[1] Pukyong Natl Univ, Dept Appl Math, Pusan 608737, South Korea

来源：

FIXED POINT THEORY AND APPLICATIONS | 2012年

基金：

新加坡国家研究基金会;

关键词：

Euclidean Jordan algebra; self-scaled optimization problem; primal-dual interior-point methods; kernel function; proximity function; complexity analysis; worst-case iteration bound; SPECTRAL FUNCTIONS; SEARCH DIRECTIONS; JORDAN ALGEBRAS; ALGORITHMS;

D O I：

10.1186/1687-1812-2012-213

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

A linear optimization problem over a symmetric cone, defined in a Euclidean Jordan algebra and called a self-scaled optimization problem (SOP), is considered. We formulate an algorithm for a large-update primal-dual interior-point method (IPM) for the SOP by using a proximity function defined by a new kernel function, and we obtain the best known complexity results of the large-update IPM for the SOP by using the Euclidean Jordan algebra techniques.

引用

页数：22

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