The Science of Breeding and Its Application to the Breeder Genetic Algorithm (BGA)

The Breeder Genetic Algorithm BGA models arti cial selection as performed by human breeders The science of breeding is based on advanced statistical methods In this paper a connection between genetic algorithm theory and the science of breeding is made We show how the response to selection equation and the concept of heritability can be applied to predict the behavior of the BGA Selection recombination and mutation are analyzed within this framework It is shown that recombination and mutation are complementary search operators The theoretical results are obtained under the assumption of additive gene e ects For general tness landscapes regression techniques for estimating the heritability are used to analyze and control the BGA The method of decomposing the genetic variance into an additive and a nonadditive part connects the case of additive tness functions with the general case