A Feasible Semismooth Gauss-Newton Method for Solving a Class of SLCPs

Year:    2012

Journal of Computational Mathematics, Vol. 30 (2012), Iss. 2 : pp. 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.

Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/10.4208/jcm.1107-m3559

Journal of Computational Mathematics, Vol. 30 (2012), Iss. 2 : pp. 197–222

Published online:    2012-01

AMS Subject Headings:   

Copyright:    COPYRIGHT: © Global Science Press

Pages:    26

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

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