IACRate {xegaPopulation}

Individually adaptive crossover rate.

Description

The basic idea is to apply crossover to a gene whose fitness is below a threshold value with higher probability to give it a chance to improve. The threshold value is computed by lF$CutoffFit()*lF$CBestFitness().

Usage

IACRate(fit, lF)

Arguments

fit

Fitness of gene.

lF

Local configuration.

Details

The following constants are used: lF$CrossRate1()<lF$CrossRate2(), and lF$CutoffFit() in [0, 1].

Value

Crossover rate of a gene depending on its fitness.

References

Stanhope, Stephen A. and Daida, Jason M. (1996) An Individually Variable Mutation-rate Strategy for Genetic Algorithms. In: Koza, John (Ed.) Late Breaking Papers at the Genetic Programming 1996 Conference. Stanford University Bookstore, Stanford, pp. 177-185. (ISBN:0-18-201-031-7)

See Also

Other Adaptive Rates: IAMRate()

Examples

parm<-function(x){function() {return(x)}}
lF<-list()
lF$CrossRate1<-parm(0.20) 
lF$CrossRate2<-parm(0.40) 
lF$CutoffFit<-parm(0.60)
lF$CBestFitness<-parm(105)
IACRate(100, lF)
IACRate(50, lF)