A retrospective view of fuzzy control of evolutionary algorithm resources

A retrospective argument supporting the adaptive control of the resources of an evolutionary algorithm is presented. In this approach, a fuzzy controller monitors the population diversity and maturity of the evolutionary process, and issues control actions to adapt the algorithm´s population size and mutation rate. The fuzzy controller´s rule base is simple and intuitive, and encodes expert heuristic knowledge on the management of an evolutionary algorithm´s resources. Analysis based on experimentation and statistical hypothesis testing reveals that such an adaptive approach significantly reduces the variance in search performance of the evolutionary algorithm. Experiments also reveal that the approach in general improves search performance of the algorithm.