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论文类型：期刊论文
发表时间：2011-03-01
发表刊物：SET-VALUED AND VARIATIONAL ANALYSIS
收录刊物：SCIE
卷号：19
期号：1
页面范围：107-134
ISSN号：1877-0533
关键字：Coderivative; Sample average approximation; Parametric stochastic generalized equation; Lipschitz-like property; SMPCC
摘要：The aim of this paper is to investigate the convergence properties for Mordukhovich's coderivative of the solution map of the sample average approximation (SAA) problem for a parametric stochastic generalized equation. It is demonstrated that, under suitable conditions, both the cosmic deviation and the rho-deviation between the coderivative of the solution mapping to SAA problem and that of the solution mapping to the parametric stochastic generalized equation converge almost surely to zero as the sample size tends to infinity. Moreover, the exponential convergence rate of coderivatives of the solution maps to the SAA parametric generalized equations is established. The results are used to develop sufficient conditions for the consistency of the Lipschitz-like property of the solution map of SAA problem and the consistency of stationary points of the SAA estimator for a stochastic mathematical program with complementarity constraints.