A SMOOTHING CONJUGATE GRADIENT ALGORITHM FOR NONLINEAR COMPLEMENTARITY PROBLEMS

被引：3
|
作者：
Wu, Caiying [1 ]
Chen, Guoqing [1 ]
机构：
[1] Inner Mongolia Univ, Coll Math Sci, Hohhot 010021, Peoples R China
来源：
JOURNAL OF SYSTEMS SCIENCE AND SYSTEMS ENGINEERING | 2008年 / 17卷 / 04期
关键词：
Nonlinear complementarity; conjugate gradient; global convergence; Fischer-Burmeister function;
D O I：
10.1007/s11518-008-5091-9
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：
A PRP-type smoothing conjugate gradient method for solving large scale nonlinear complementarity problems (NCP(F)) is proposed. At each iteration, two Armijo line searches are performed, which guarantees the positive property of the smoothing parameter and minimizes the merit function formed by Fischer-Burmeister function, respectively. Global convergence is studied when F: R-n -> R-n is a continuously differentiable P-0 + R-0 function. Numerical results show that the method is efficient.
引用
收藏
页码：460 / 472
页数：13
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