Application of penalty method to nonstationary approximation of optimization problem

We solve a general optimization problem, where only approximation sequences are known instead of exact values of the goal function and feasible set. Under these conditions we suggest to utilize a penalty function method. We show that its convergence is attained for rather arbitrary means of approximation via suitable coercivity type conditions.