Stability in distribution problems of nonlinear stochastic programming

This paper is concerned with the stability property of the optimum of nonlinear distribution problems with respect to the random vector. It gives conditions, under which the optimum of the problem with approximate random vectors will converge to the optimum of the original problem in distribution sense, L1-sense or in the sense of mean-convergence respectively. Based upon this stability an approximation method is suggested.