Stochastic Optimization Method in Computer Decision Support System

The questions of parameter optimization are considered in the article. These parameters describe technological processes at ore-dressing plants. There are many problems in creating of automated control systems for such technological processes. Among them are a large number of industrial parameters, the nondeterministic nature of physical and mechanical properties of the raw materials, and many disturbing influences. Thus, to solve these problems authors propose to use an intelligent computer decision support system. It allows calculating a regression equation of some optimization criterion. The complete Kolmogorov-Gabor polynomial is used as a regression model. In addition, the possibility of applying the differential evolution method is analysed. The stochastic optimization method has been compared with the full enumeration method, gradient descent method and Monte Carlo. A simple function with an extremum has been used as an example for demonstrating of search efficiency.