Stochastic optimization methods with constraints

Recurrent methods are surveyed employed in solving optimization problems with constraints and noise. The attention focuses on convergence and the rate of convergence of gradient and search procedures with data on the noise available in advance. Various types of constraints on the range of the argument of the function to be optimized are discussed.