Application of distributed and parallel processing techniques for stochastic optimization problems

The class of stochastic systems characterized by operators with deterministic structures and random parameters is considered The paper discusses the problem of choosing parameter nominals of engineering devices and systems for which the system survival probability or the performance assurance probability for the predetermined time period is maximized. Special attention os paid to algorithms that reduce the computation cost of stochastic optimization problems Several techniques to reduce labour requirements of Monte Carlo modeling and discrete optimization using parallel and distributed processing are discussed. On the basis of the proposed methods and algorithms a computer-aided reliability-oriented design system has been developed.