Metaheuristic algorithm parameters selection for building an optimal hierarchical structure of a control system: a case study

Abstract

Metaheuristic algorithms are currently widely used to solve a variety of optimization problems across various industries. This article discusses the application of a metaheuristic algorithm to optimize the hierarchical architecture of an industrial distributed control system. The success of the algorithm depends largely on the choice of starting conditions and algorithm parameters. We examine the impact of parameter selection on the convergence of a modified ant colony algorithm and provide recommendations for tuning the algorithm to achieve optimal results for a specific industrial problem. The findings presented in this article can also be applied to other combinatorial optimization problems.