An O(√nL) predictor-corrector interior-point algorithm for semidefinite optimization based on a wide neighbourhood

被引：0
|
作者：
Kheirfam, B. [1 ]
Sangachin, M. Mohamadi [1 ]
机构：
[1] Azarbaijan Shahid Madani Univ, Dept Math, Tabriz, Iran
来源：
INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS | 2021年 / 98卷 / 02期
关键词：
Semidefinite optimization; predictor-corrector interior-point method; wide neighbourhood; polynomial complexity;
D O I：
10.1080/00207160.2020.1748604
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In this paper, we propose a new predictor-corrector interior-point algorithm for semidefinite optimization based on a wide neighbourhood of the central path. We show that, in addition to the predictor step, each corrector step decreases the duality gap as well. We also prove that the iteration complexity of the proposed algorithm coincides with the best iteration bound for small neighbourhood algorithms that use the Nesterov-Todd direction. Finally, some numerical results are provided as well.
引用
收藏
页码：414 / 433
页数：20
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