Tutorial Sobre o Uso de Técnicas para Controle Online de Parâmetros em Algoritmos de Inteligência de Enxame e Computação Evolutiva

Nature has always been a great source of inspiration for the develop-ment of computational approaches for optimization. Two major groups representingthis class of biologically inspired algorithms are Swarm Intelligence and Evolutio-nary Computation. Such algorithms are called metaheuristics and are recognized tobe efficient approaches for solving complex problems. Both Swarm Intelligence andEvolutionary Computation share common features such as the use of stochastic com-ponents during the optimization process and various parameters for configuration. Thesetup of parameters of an algorithm has an important role in defining its behavior, gui-ding the search and biasing the quality of the solutions found. However, adjustingthe parameters is not a simple task, becoming an optimization problem within theproblem being optimized. In addition, an appropriate setting for the parameters maychange during the optimization process making this task even harder. There are twoways to adjust the parameters of an algorithm. The offline control that is performedbefore running the algorithm and parameter values remains fixed and the online con-trol where parameter values may change during the optimization process. This articlefocuses on reviewing the online parameter control strategies applied in EvolutionaryComputation and Swarm Intelligence. As a result, this review analyzes and pointsout the key techniques and algorithms used and suggests some directions for futureresearch.