A problem of probability function optimization is considered. This function represents probability that some random quantity depending on deterministic parameters does not exceed some given level. The problem is motivated by studies of safety domains and risk control problems in complex stochastic systems. For example, pollution control includes maximization of probability that some given levels of deposition at reception points are not exceeded. Optimization of probability function is performed over a given range of parameters. To solve the problem stochastic quasi-gradient method is applied under quasi-concavity assumption on functions and measures involved. Convergence and rate of convergence results are presented
