A POLYNOMIAL-TIME INTERIOR-POINT ALGORITHM FOR CONVEX QUADRATIC SEMIDEFINITE OPTIMIZATION

被引：5
|
作者：
Bai, Y. Q. [1 ]
Wang, F. Y. [1 ]
Luo, X. W. [1 ]
机构：
[1] Shanghai Univ, Dept Math, Shanghai 200444, Peoples R China
来源：
RAIRO-OPERATIONS RESEARCH | 2010年 / 44卷 / 03期
基金：
中国国家自然科学基金;
关键词：
Convex quadratic semidefinite optimization; interior-point algorithm; small-update method; iteration bound; polynomial-time; SDP;
D O I：
10.1051/ro/2010016
中图分类号：
C93 [管理学]; O22 [运筹学];
学科分类号：
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要：
In this paper we propose a primal-dual interior-point algorithm for convex quadratic semidefinite optimization problem. The search direction of algorithm is defined in terms of a matrix function and the iteration is generated by full-Newton step. Furthermore, we derive the iteration bound for the algorithm with small-update method, namely, O(root n log n/epsilon), which is best-known bound so far.
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页码：251 / 265
页数：15
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