Study of M-stationarity and strong stationarity for a class of SMPCC problems via SAA Method

In this article my main aim is to analyze the relative importance of M-stationarity concept over strong stationarity of one stage stochastic mathematical programming problems with complementarity constraints (SMPCC, in short). We establish the consistency of M-stationary multipliers when the SMPCC problem is approximated through the sample average approximation (SAA, for short) method, under the assumption of SMPCC-NNAMCQ. On contrary, strong stationary multipliers are not consistent even in presence of SMPCC-LICQ.