Abstract

Tournament selection is a useful and robust selection mechanism commonly used by genetic algorithms. The selection pressure of tournament selection directly varies with the tournament size --- the more competitors, the higher the resulting selection pressure. This article develops a model, based on order statistics, that can be used to quantitatively predict the resulting selection pressure of a tournament of a given size. This model is used to predict the convergence rates of genetic algorithms utilizing tournament selection. While tournament selection is often used in conjunction with noisy (imperfect) fitness functions, little is understood about how the noise affects the resulting selection pressure. The model is extended to quantitatively predict the selection pressure for tournament selection utilizing noisy fitness functions. Given the tournament size and noise level of a noisy fitness function, the extended model is used to predict the resulting selection pressure of tournament...

Citations