Methods of system composition and decomposition as a tool for efficient processing of large amounts of experimental data

Abstract

The industrial age led to the emergence of geographically distributed industrial complexes operating in conditions of limited resources and internal competition. Accordingly, the problem of optimizing the regional distribution of industrial objects arose, which was fully solved only with the development of computer technology, which made it possible to quickly and efficiently process large amounts of experimental data. Mathematical approach to solving the economic problems helped to solve some difficult problems. To solve these problems, in the second half of the last century, a whole set of mathematical methods was developed, which made it possible to finally turn Economics into an exact science. When solving large-scale national economic problems, a systematic approach and mathematical methods such as stochastic programming, discrete programming, convex programming, nonlinear and linear programming were used. The decomposition method is one of the most popular ways to solve tasks and goals of any type, which are based on their detailed analysis and division of the process into several stages. This method is most often used in such fields as Economics, mathematics, etc. There is such a method as the approximation-combinatorial method of decomposition and composition of systems. the considered approximation method offers a modification of the listed methods, which can lead to a decrease in their “sensitivity” to changes in the problem conditions, which certainly makes it possible to expand the class of problems that can be solved using the listed methods.