Examining the impact of neutrality on genetic algorithm population evolution
MetadataShow full item record
This item's downloads: 75 (view details)
Cited 0 times in Scopus (view citations)
Hill, Seamus , & O'Riordan, Colm. (2015). Examining the impact of neutrality on genetic algorithm population evolution. Paper presented at the 7th International Conference on Evolutionary Computation Theory and Applications ECTA, Lisbon, Portugal, DOI: 10.5220/0005594301960203, In Proceedings of the 7th International Joint Conference on Computational Intelligence - Volume 1: ECTA,.
This paper examines the introduction of neutrality as proposed by Kimura (Kimura, 1968) into the genotype-phenotype mapping of a Genetic Algorithm (GA). The paper looks at the evolution of both a simple GA (SGA) and a multi-layered GA (MGA) incorporating a layered genotype-phenotype mapping based on the biological concepts of Transcription and Translation. Previous research in comparing GAs often use performance statistics; in this paper an analysis of population dynamics is used for comparison. Results illustrate that the MGA population’s evolution trajectory is quite different to that of the SGA population over dynamic landscapes and that the introduction of neutrality implicitly maintains genetic diversity within the population primarily through genetic drift in association with selection.