A method tо solve stochastic optimization problems with constraints

A recurrent method is discussed of solving optimization problems with constraints and in the presence of random noise. Its convergence and rate of convergence are studied, in particular the case where the minima of the membership function stay оn the boundary of the feasible set. The basic results are reported for the case of minimizing a quadratic function for a simple deterministic set.