xegaGaReplicateGene: Replicates a gene.

In xegaGaGene: Binary Gene Operations for Genetic Algorithms

Replicates a gene.

Description

xegaGaReplicateGene() replicates a gene by applying a gene reproduction pipeline which uses crossover and mutation and finishes with an acceptance rule. The control flow starts by selecting a gene from the population followed by the case distinction:

• Check if the mutation operation should be applied. (mut is TRUE with a probability of lF$MutationRate()).

• Check if the crossover operation should be applied. (cross is TRUE with a probability of lF$CrossRate()).

The state distinction determines which genetic operations are performed.

Usage

xegaGaReplicateGene(pop, fit, lF)

Arguments

pop	Population of binary genes.
fit	Fitness vector.
lF	Local configuration of the genetic algorithm.

Details

xegaGaReplicateGene() implements the control flow by a dynamic definition of the operator pipeline depending on the random choices for mutation and crossover:

1. A gene g is selected and the boolean variables mut and cross are set to runif(1)<rate.

2. The local function for the operator pipeline OPpip(g, lF) is defined by the truth values of cross and mut:

   1. (cross==FALSE) & (mut==FALSE): Identity function.

   2. (cross==TRUE) & (mut==TRUE): Mate selection, crossover, mutation.

   3. (cross==TRUE) & (mut==FALSE): Mate selection, crossover.

   4. (cross==FALSE) & (mut==TRUE): Mutation.

3. Perform the operator pipeline and accept the result. The acceptance step allows the combination of a genetic algorithm with other heuristic algorithms like simulated annealing by executing an acceptance rule. For the genetic algorithm, the identity function is used.

Value

A list of one gene.

See Also

Other Replication: xegaGaReplicate2Gene()

Examples

lFxegaGaGene$CrossGene<-xegaGaCrossGene
lFxegaGaGene$MutationRate<-function(fit, lF) {0.001}
lFxegaGaGene$Accept<-function(OperatorPipeline, gene, lF) {gene}
pop10<-lapply(rep(0,10), function(x) xegaGaInitGene(lFxegaGaGene))
epop10<-lapply(pop10, lFxegaGaGene$EvalGene, lF=lFxegaGaGene)
fit10<-unlist(lapply(epop10, function(x) {x$fit}))
newgenes<-xegaGaReplicateGene(pop10, fit10, lFxegaGaGene)

xegaGaGene documentation built on April 16, 2025, 5:11 p.m.