An interior point method with a primal-dual quadratic barrier penalty function for nonlinear semidefinite programming

被引：8
|
作者：
Kato, Atsushi [1 ]
Yabe, Hiroshi [2 ]
Yamashita, Hiroshi [3 ]
机构：
[1] Giga Hertz Technol Inc, Kouhoku Ku, Yokohama, Kanagawa 2220033, Japan
[2] Tokyo Univ Sci, Fac Sci, Dept Math Informat Sci, Shinjuku Ku, Tokyo 1628601, Japan
[3] NTT DATA Math Syst Inc, Shinjuku Ku, Tokyo 1600016, Japan
来源：
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS | 2015年 / 275卷
基金：
日本学术振兴会;
关键词：
Nonlinear semidefinite programming; Primal-dual interior point method; Primal-dual quadratic barrier penalty function; Global convergence; ROBUST-CONTROL; OPTIMIZATION; ALGORITHM; MATRIX;
D O I：
10.1016/j.cam.2014.07.024
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In this paper, we consider an interior point method for nonlinear semidefinite programming. Yamashita, Yabe and Harada presented a primal-dual interior point method in which a nondifferentiable merit function was used. By using shifted barrier KKT conditions, we propose a differentiable primal-dual merit function within the framework of the line search strategy, and prove its global convergence property under weaker assumptions than the method of Yamashita, Yabe and Harada. (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码：148 / 161
页数：14
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