A constrained simultaneous perturbation stochastic approximation algorithm based on penalty functions

We present a stochastic approximation algorithm based on the penalty function method and a simultaneous perturbation gradient estimate for solving stochastic optimization problems with general inequality constraints. We also presents a very general convergence result for the proposed algorithm.