摘要

In this paper, a type of one stage stochastic generalized Nash equilibrium problem (SGNEP) is solved by the sample average approximation (SAA) method. It is demonstrated that the sequence of Karush-Kuhn-Tucker points of SAA problems converges to a Karush-Kuhn-Tucker point of the true problem with probability one at an exponential rate as the sample size tends to infinity. To implement the SAA method in practice, the smoothing Newton method is introduced. In the case when the expectation constraint functions in the true problem are strongly additive, the nonsingularity of Clarke's generalized Jacobian of the SAA Karush-Kuhn-Tucker system, which is required in the convergence analysis of smoothing Newton method, is demonstrated under the so-called SGNEP-LICQ and SGNEP-SOSC. For this special case, preliminary numerical results are reported to show the efficiency of the method.