A class of smoothing SAA methods for  a   stochastic linear complementarity problem

Jie Zhang; Yue Wu; Liwei Zhang

doi:10.3934/naco.2012.2.145

Article Contents

2012, Volume 2, Issue 1: 145-156. Doi: 10.3934/naco.2012.2.145

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A class of smoothing SAA methods for a stochastic linear complementarity problem

1.
School of Mathematics, Liaoning Normal University, Dalian, 116029
2.
School of Management, University of Southampton, Highfield Southampton SO17 1BJ
3.
School of Mathematical Sciences, Dalian University of Technology, Dalian 116024

Received: January 2011

Revised: October 2011

Published: February 2012

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Abstract

A class of smoothing sample average approximation (SAA) methods is proposed for solving a stochastic linear complementarity problem, where the underlying function is the expected value of stochastic function. Existence and convergence results to the proposed methods are provided and some numerical results are reported to show the efficiency of the methods proposed.

Keywords:

Smoothing SAA method,
stochastic linear complementarity problem.

Mathematics Subject Classification: Primary: 90C33, 90C15.

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