Data accumulation and sorting method for solving parametric optimization problem

It is noted that optimization problem is highly relevant for complex system development. However, such optimization is difficult since there are no reliable methods that give efficient solutions regardless of the features of a specific mathematical model. Developing a method for solving arbitrary parametric optimization problems is a complicated but highly relevant task. The new approach is considered, which is based on heuristics and experiments. It uses special truncation and sorting procedures, Pareto methods, and random process theory methods. The software implementation and multiple modifications of the method proposed are developed and tested with a number of highly complex test functions covering the entire range of parametric optimization problems. It is shown experimentally that the approach proposed is highly efficient. The method can be applied for solving complex research problems and its software can become a part of large integrated systems such as CADs, smart systems, etc. where multivariate analysis is used for decision making.