Algorithms for Optimizing the Values of Parametric Series of Machine Tools

This paper presents stochastic criteria for optimizing the values of parametric series of power industry machine tools. In view of practical impossibility of analytical solution of optimization problem in general case with non-convex economic indicators and random functions of probability distribution density functions, neither the type nor the parameters of which are unknown, it is proposed to use recurrence relation - stochastic approximation algorithms. The method of estimation of the sought values of the members of the size series, the nature and convergence rate of stochastic approximation algorithms are discussed.