Синтез согласованных линейных оптимизационных моделей по прецедентной информации: подход на основе колмогоровской сложности

In the paper, approach is expounded to the analysis of the linear optimization models built on precedent initial learning information. In supposition, that all numerical parameters are rational and limited by the bit net of computer, estimations of Kolmogorov’s complexity and nonrandomness of extraction of model as empirical regularity are got from the sample.