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A FEASIBLE SEMISMOOTH GAUSS-NEWTON METHOD FOR SOLVING A CLASS OF SLCPS

A FEASIBLE SEMISMOOTH GAUSS-NEWTON METHOD FOR SOLVING A CLASS OF SLCPS
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摘要 In this paper, we consider a class of the stochastic linear complementarity problems (SLCPs) with finitely many elements. A feasible semismooth damped Gauss-Newton al- gorithm for the SLCP is proposed. The global and locally quadratic convergence of the proposed algorithm are obtained under suitable conditions. Some numerical results are reported in this paper, which confirm the good theoretical properties of the proposed al- gorithm.Mathematics subject classification: 90C33, 65K10. In this paper, we consider a class of the stochastic linear complementarity problems (SLCPs) with finitely many elements. A feasible semismooth damped Gauss-Newton al- gorithm for the SLCP is proposed. The global and locally quadratic convergence of the proposed algorithm are obtained under suitable conditions. Some numerical results are reported in this paper, which confirm the good theoretical properties of the proposed al- gorithm.Mathematics subject classification: 90C33, 65K10.
作者 Changfeng Ma
出处 《Journal of Computational Mathematics》 SCIE CSCD 2012年第2期197-222,共26页 计算数学(英文)
基金 Acknowledgments. This project is supported by National Natural Science Foundation of China (11071041) and Fujian Natural Science Foundation (2009J01002).
关键词 Stochastic linear complementarity problems Gauss-Newton algorithm Con-vergence analysis Numerical results. Stochastic linear complementarity problems, Gauss-Newton algorithm, Con-vergence analysis, Numerical results.
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