A predictor-corrector interior-point algorithm for the semidefinite linear complementarity problem using the Alizadeh-Haeberly-Overton search direction

被引：32

作者：

Kojima, M

Shida, M

Shindoh, S

机构：

[1] Tokyo Inst Technol, Dept Math & Comp Sci, Meguro Ku, Tokyo 152, Japan

[2] Kanagawa Univ, Fac Engn, Dept Math, Kanagawa Ku, Yokohama, Kanagawa 221, Japan

[3] Natl Def Acad, Dept Math & Phys, Yokosuka, Kanagawa 239, Japan

来源：

SIAM JOURNAL ON OPTIMIZATION | 1999年 / 9卷 / 02期

关键词：

semidefinite linear complementarity problem; semidefinite programming; interior-point algorithm; predictor-corrector algorithm; local convergence; quadratic convergence;

D O I：

10.1137/S1052623496300623

中图分类号：

O29 [应用数学];

学科分类号：

070104 [应用数学];

摘要：

This paper proposes a globally convergent predictor-corrector infeasible-interior-point algorithm for the monotone semidefinite linear complementarity problem using the Alizadeh-Haeberly-Overton search direction, and shows its quadratic local convergence under the strict complementarity condition.

引用

页码：444 / 465

页数：22

共 34 条

[1]

INTERIOR-POINT METHODS IN SEMIDEFINITE PROGRAMMING WITH APPLICATIONS TO COMBINATORIAL OPTIMIZATION [J].