On complexity analysis of the primal-dual interior-point method for semidefinite optimization problem based on a new proximity function

被引：14
|
作者：
Choi, Bo Kyung [1 ]
Lee, Gue Myung [1 ]
机构：
[1] Pukyong Natl Univ, Div Math Sci, Pusan 608737, South Korea
来源：
NONLINEAR ANALYSIS-THEORY METHODS & APPLICATIONS | 2009年 / 71卷 / 12期
关键词：
Semidefinite optimization problem; Primal-dual interior-point methods; Kernel function; Proximity function; Complexity analysis; Worst-case iteration bound; ALGORITHMS;
D O I：
10.1016/j.na.2009.05.078
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
The purpose of this paper is to obtain new complexity results for a semidefinite optimization (SDO) problem. We define a new proximity function for the SDO by a new kernel function. Furthermore we formulate an algorithm for a large-update primal-dual interior-point method (IPM) for the SDO by using the proximity function and give its complexity analysis, and then we show that the worst-case iteration bound for our IPM is O(root n(log n)(q+1/q) log n/c), where q >= 1 (C) 2009 Elsevier Ltd. All rights reserved.
引用
收藏
页码：E2628 / E2640
页数：13
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