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A smoothing conjugate gradient algorithm for nonlinear complementarity problems

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Abstract

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.

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Authors and Affiliations

  1. College of Mathematics Science, Inner Mongolia University, Hohhot, 010021, China

    Caiying Wu & Guoqing Chen

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  1. Caiying Wu
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  2. Guoqing Chen
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Correspondence to Caiying Wu.

Additional information

The project is supported by the Teaching and Research Award Program for the Outstanding Young Teachers in Higher Education Institutes of Ministry of Education, P. R. China.

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Wu, C., Chen, G. A smoothing conjugate gradient algorithm for nonlinear complementarity problems. J. Syst. Sci. Syst. Eng. 17, 460–472 (2008). https://doi.org/10.1007/s11518-008-5091-9

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  • DOI: https://doi.org/10.1007/s11518-008-5091-9

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