A Study of Genetic Algorithm Parameterization via a Benchmark of Test Functions

Abstract

This paper presents a study to properly parameterize the Genetic Algorithm (GA) in a way to increase its performance. Parameterization is a crucial phase before any use for problem solving. An analysis of the influence of the main parameters of GA on the quality of solutions found has been shown. The parameters taken into consideration are the population size, the type of selection, the type of crossover and the mutation rate. A set of mathematical functions (unimodal and multimodal) whose global minimum is known in advance is used for this purpose.