Adapting Operator Settings in Genetic Algorithms


In the majority of genetic algorithm implementations, the operator settings are fixed throughout a given run. However, it has been argued that these settings should vary over the course of a genetic algorithm run--so as to account for changes in the ability of the operators to produce children of increased fitness. This paper describes an investigation into… (More)
DOI: 10.1162/evco.1998.6.2.161


17 Figures and Tables


Citations per Year

136 Citations

Semantic Scholar estimates that this publication has 136 citations based on the available data.

See our FAQ for additional information.