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Volume 30, Issue 2
A Feasible Semismooth Gauss-Newton Method for Solving a Class of SLCPs

Changfeng Ma

DOI: 10.4208/jcm.1107-m3559

J. Comp. Math., 30 (2012), pp. 197-222.

Published online: 2012-04

[An open-access article; the PDF is free to any online user.]

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  • Abstract

In this paper, we consider a class of the stochastic linear complementarity problems (SLCPs) with finitely many elements. A feasible semismooth damped Gauss-Newton algorithm for the SLCP is proposed. The global and local 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 algorithm.

  • Keywords

Stochastic linear complementarity problems, Gauss-Newton algorithm, Convergence analysis, Numerical results.

  • AMS Subject Headings

90C33, 65K10.

  • Copyright

COPYRIGHT: © Global Science Press

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@Article{JCM-30-197, author = {Changfeng Ma}, title = {A Feasible Semismooth Gauss-Newton Method for Solving a Class of SLCPs}, journal = {Journal of Computational Mathematics}, year = {2012}, volume = {30}, number = {2}, pages = {197--222}, abstract = {

In this paper, we consider a class of the stochastic linear complementarity problems (SLCPs) with finitely many elements. A feasible semismooth damped Gauss-Newton algorithm for the SLCP is proposed. The global and local 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 algorithm.

}, issn = {1991-7139}, doi = {https://doi.org/10.4208/jcm.1107-m3559}, url = {http://global-sci.org/intro/article_detail/jcm/8425.html} }
TY - JOUR T1 - A Feasible Semismooth Gauss-Newton Method for Solving a Class of SLCPs AU - Changfeng Ma JO - Journal of Computational Mathematics VL - 2 SP - 197 EP - 222 PY - 2012 DA - 2012/04 SN - 30 DO - http://doi.org/10.4208/jcm.1107-m3559 UR - https://global-sci.org/intro/article_detail/jcm/8425.html KW - Stochastic linear complementarity problems, Gauss-Newton algorithm, Convergence analysis, Numerical results. AB -

In this paper, we consider a class of the stochastic linear complementarity problems (SLCPs) with finitely many elements. A feasible semismooth damped Gauss-Newton algorithm for the SLCP is proposed. The global and local 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 algorithm.

Changfeng Ma. (2012). A Feasible Semismooth Gauss-Newton Method for Solving a Class of SLCPs. Journal of Computational Mathematics. 30 (2). 197-222. doi:10.4208/jcm.1107-m3559
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