An O (√nL) wide neighborhood interior-point algorithm for semidefinite optimization

被引：0
|
作者：
Pirhaji, M. [1 ]
Mansouri, H. [1 ]
Zangiabadi, M. [1 ]
机构：
[1] Shahrekord Univ, Fac Math Sci, Dept Appl Math, POB 115, Shahrekord, Iran
来源：
COMPUTATIONAL & APPLIED MATHEMATICS | 2017年 / 36卷 / 01期
关键词：
Semidefinite optimization; Interior-point methods; Wide neighborhood; Polynomial complexity; PATH-FOLLOWING METHOD; CONES;
D O I：
10.1007/s40314-015-0220-9
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In this paper, we propose a primal-dual interior-point method for semidefinite optimization problems. The algorithm is based on a new class of search directions and the Ai-Zhang's wide neighborhood for monotone linear complementarity problems. The theoretical complexity of the new algorithm is calculated. It is investigated that the proposed algorithm has polynomial iteration complexity and coincides with the best known iteration bound for semidefinite optimization problems.
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页码：145 / 157
页数：13
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