Comparative study of the heuristic bioinspired algorithms effectiveness in the optimization of multi-extremal functions

The most popular optimization algorithms, which allow finding the approximate value of the extremum for test problems and functions were considered in this paper. Bioinspired algorithms were selected as the object of the research as the most promising for solving optimization problems. The purpose of this work is to study and compare various bioinspired algorithms with each other by creating a software, because there are no accurate estimates of the relationship between the running time of the algorithm and the obtained solution accuracy for them. The practical result of the work is the development of a software analytical system for the necessary comparative analysis of bioinspired algorithms. The developed software allows to connect new algorithms and functions and accumulate libraries of optimization algorithms and test functions and tasks. In the course of the work, it was found that one of the most promising ways to solve optimization problems is bioinspired algorithms, in cases where the exact methods for solving the problem are unknown or too laborious. In the course of computational experiment, the designed software showed good performance and help in constructing analytical graphs. Various dependencies were established, illustrating the optimal choice of quantitative indicators of genetic algorithm population individuals, the deviation of which from the optimal function value becomes minimal.