SelectPropFitDiffOnln: Selection proportional to fitness differences O(n ln(n)).

In xegaSelectGene: Selection of Genes and Gene Representation Independent Functions

Selection proportional to fitness differences O(n ln(n)).

Description

SelectPropFitDiffOnln() implements selection proportional to fitness differences. Negative fitness vectors are shifted to R^+. The default of the function lF$Offset() is 1. Holland's schema theorem uses this selection function. See John Holland (1975) for further information.

Usage

SelectPropFitDiffOnln(fit, lF, size = 1)

Arguments

fit	Fitness vector.
lF	Local configuration.
size	Number of selected genes. Default: 1.

Details

This is a fast implementation which gives exactly the same results as the functions SelectPropFitDiff() and SelectPropDiffFitM(). Its runtime is O(n . ln(n)).

An epsilon (lF$Eps()) is added to the fitness difference vector. This guarantees numerical stability, even if all genes in the population have the same fitness.

Value

The index vector of the selected genes.

Credits

The code of this function has been adapted by Fabian Aisenbrey.

Warning

There is a potential slow for-loop in the code.

References

Holland, John (1975): Adaptation in Natural and Artificial Systems, The University of Michigan Press, Ann Arbor. (ISBN:0-472-08460-7)

See Also

Other Selection Functions: SelectDuel(), SelectLRSelective(), SelectLinearRankTSR(), SelectPropFit(), SelectPropFitDiff(), SelectPropFitDiffM(), SelectPropFitM(), SelectPropFitOnln(), SelectSTournament(), SelectSUS(), SelectTournament(), SelectUniform(), SelectUniformP()

Examples

fit<-sample(10, 15, replace=TRUE)
SelectPropFitDiffOnln(fit, NewlFselectGenes()) 
SelectPropFitOnln(fit, NewlFselectGenes(), length(fit)) 

xegaSelectGene documentation built on April 16, 2025, 5:12 p.m.