| IAMRate {xegaPopulation} | R Documentation |
Individually adaptive mutation rate.
Description
The probability of applying a mutation operator to a gene. The idea is that a gene selected for reproduction whose fitness is below a threshold value is mutated with a higher probability to give it a chance.
Usage
IAMRate(fit, lF)
Arguments
fit |
Fitness of gene. |
lF |
Local configuration. |
Details
The probability of applying a mutation operator is
determined by a threshold: If the fitness of a gene
is higher than lF$CutoffFit()*lF$CBestFitness(),
than return lF$MutationRate1()
else lF$MutationRate2().
Note that the idea is also applicable to gene specific local mutation operators. For example, the bit mutation rate of mutation operators for binary genes.
Value
Mutation 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:
IACRate()
Examples
parm<-function(x){function() {return(x)}}
lF<-list()
lF$MutationRate1<-parm(0.20)
lF$MutationRate2<-parm(0.40)
lF$CutoffFit<-parm(0.60)
lF$CBestFitness=parm(105)
IAMRate(100, lF)
IAMRate(50, lF)