Analysing the impact of dimensionality on diversity in a multi-layered Genotype-Phenotype mapped genetic algorithm

This paper examines the impact of changes in dimensionality on a multi-layered genotype-phenotype mapped GA. To gain an understanding of the impact we carry out a series of experiments on a number of well understood problems and compare the performance of a simple GA (SGA) to that of a multi-layered GA (MGA) to demonstrate their ability to search landscapes with varying degrees of difficulty due to changes in the dimensionality of each function. The paper also examines the impact of diversity maintenance in assisting the search and identifies the natural increase in diversity as the level of problem difficulty increases, as a result of the layered Genotype-Phenotype mapping. Initial results indicate that it may be advantageous to include a multi-layered genotype-phenotype mapping under certain circumstances. peer-reviewe