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January  2010, 6(1): 241-257. doi: 10.3934/jimo.2010.6.241

Penalty-based SAA method of stochastic nonlinear complementarity problems

Ming-Zheng Wang 1, and  M. Montaz Ali 2,

1. 

School of Management, Dalian University of Technology, Dalian 116024, Liaoning Province, China
2. 

School of Computational and Applied Mathematics, University of the Witwatersrand, Wits-2050, Johannesburg, South Africa

Received  October 2008 Revised  October 2009 Published  November 2009

We consider a class of stochastic nonlinear complementarity problems. We first formulate the stochastic complementarity problem as a stochastic programming model. Based on this reformulation, we propose a penalty-based sample average approximation (in short, SAA) method for stochastic complementarity problem and prove its convergence. Finally, we report some numerical test results to show the efficiency of our method.
Keywords: sample average approximation, Stochastic nonlinear complementarity problems, convergence., stochastic programming, penalty method.
Mathematics Subject Classification: 90C33, 90C30, 90C1.
Citation: Ming-Zheng Wang, M. Montaz Ali. Penalty-based SAA method of stochastic nonlinear complementarity problems. Journal of Industrial & Management Optimization, 2010, 6 (1) : 241-257. doi: 10.3934/jimo.2010.6.241
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