Diversity control based on population heterozygosity dynamics
Maury Meirelles Gouvêa, A.F.R. Araujo · 2008
Maintaining the population diversity in genetic algorithms (GAs), or minimize its loss, may benefit the evolutionary process in several ways. The premature convergence may lead the GA to a non-optimal result, that is, converging to a local optimum. Specially in dynamic problems, the diversity preservation is a crucial issue. In this work, a study of different diversity models based on several works has been made. From these models a diversity reference-model has been created in order to enhance diversity-reference adaptive control (DRAC) [20] performance. This new version of DRAC method was evaluated in case studies using a dynamic test functions presented in [26]. The validation of the proposed adaptive parameter control method was performed comparing its performance with SGA and other diversity-based algorithm.