A smoothing conjugate gradient algorithm for nonlinear complementarity problems

被引:0
|
作者
Caiying Wu
Guoqing Chen
机构
[1] Inner Mongolia University,College of Mathematics Science
关键词
Nonlinear complementarity; conjugate gradient; global convergence; Fischer-Burmeister function;
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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: Rn → Rn is a continuously differentiable P0+R0 function. Numerical results show that the method is efficient.
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页码:460 / 472
页数:12
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