A predictor-corrector smoothing Newton method for symmetric cone complementarity problems

被引：12

作者：

Liu, Lixia ^{[1
]}

Liu, Sanyang ^{[1
]}

Liu, Hongwei ^{[1
]}

机构：

[1] Xidian Univ, Dept Appl Math, Xian 710071, Shaanxi, Peoples R China

来源：

APPLIED MATHEMATICS AND COMPUTATION | 2010年 / 217卷 / 07期

关键词：

Symmetric cone complementarity problems; Smoothing Newton method; Predictor-corrector; Global convergence; Local quadratic convergence; INTERIOR-POINT ALGORITHMS; MERIT FUNCTIONS; CONVERGENCE;

D O I：

10.1016/j.amc.2010.08.032

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper, we present a predictor-corrector smoothing Newton method for solving nonlinear symmetric cone complementarity problems (SCCP) based on the symmetrically perturbed smoothing function. Under a mild assumption, the solution set of the problem concerned is just nonempty, we show that the proposed algorithm is globally and locally quadratic convergent. Also, the algorithm finds a maximally complementary solution to the SCCP. Numerical results for second order cone complementarity problems (SOCCP), a special case of SCCP, show that the proposed algorithm is effective. (C) 2010 Elsevier Inc. All rights reserved.

引用

页码：2989 / 2999

页数：11

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