Expected residual minimization method for a class of stochastic quasivariational inequality problems

We consider the expected residual minimization method for a class of stochastic quasivariational inequality problems (sqvip). the regularized gap function for quasivariational inequality problem (qvip) is in general not differentiable. we first show that the regularized gap function is differentiable and convex for a class of qvips under some suitable conditions. then,we reformulate sqvip as a deterministic minimization problem that minimizes the expected residual of the regularized gap function and solve it by sample average approximation (saa) method. finally,we investigate the limiting behavior of the optimal solutions and stationary points. © 2012 hui-qiang ma and nan-jing huang.