A SMOOTHING CONJUGATE GRADIENT ALGORITHM FOR NONLINEAR COMPLEMENTARITY PROBLEMS

被引：0
|
作者：
Caiying WU~1 Guoqing CHEN~2 1 College of Mathematics Science
机构：
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：
暂无
中图分类号：
O224 [最优化的数学理论];
学科分类号：
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+ Rfunction.Numerical results show that the method is efficient.
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页码：460 / 472
页数：13
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