Comparison of Evolutionary Optimization Methods on the Example of Rastrigin Function

The use of modern approaches to business process optimization is one of the key areas of any organization. Artificial intelligence provides modern business with opportunities to optimize the most complex and time-consuming tasks in the field of numerical optimization. In this regard, there is a growing need for research that provides information on comparing the effectiveness of artificial intelligence methods with each other in certain classes of problems. The paper describes the comparison of three key evolutionary optimization methods on the classical example of optimization of extremum search in the Rastrigin function: genetic algorithm, evolutionary strategies, and particle swarm algorithm. The theoretical foundations of the algorithms are reviewed, and their features are described. The comparison between the accuracy of the solution and the time in which it was obtained is used as a comparison criterion. In the course of the study, results are obtained to determine the most efficient method for solving this problem.