A Fuzzy Intelligent Controller for Genetic Algorithms’ Parameters

Genetic Algorithms have been successful in several practical appliances and obtained great prominence among the techniques of Evolutionary Computation. A large portion of methods and parameters adopted in its use are heuristic or random choices, which remain unchanged throughout the execution once they are set. This can lead to a certain lack of exploration of the search surface and also compromise the variability of the population. For that matter, this work introduces the implementation of an intelligent agent based on fuzzy logic, enabling dynamic monitoring and regulation of six GA parameters. The results obtained surpass the GA traditional implementation in many aspects, and open a wide new space for research and study.