mutation: Mutation Method

In windfarmGA: Genetic Algorithm for Wind Farm Layout Optimization

Description

The function randomly mutates an individual's genetic code

Usage

mutation(a, p, seed = NULL)

Arguments

a	The binary matrix of all individuals
p	The mutation rate
seed	Set a seed for comparability. Default is NULL

Value

Returns a binary matrix with mutated genes.

See Also

Other Genetic Algorithm Functions: crossover(), fitness(), genetic_algorithm(), init_population(), selection(), trimton(), windfarmGA()

Examples

## Create 4 random individuals with binary values
a <- cbind(bin0 = sample(c(0,1), 20, replace=TRUE, prob = c(70,30)),
           bin1 = sample(c(0,1), 20, replace=TRUE, prob = c(30,70)),
           bin2 = sample(c(0,1), 20, replace=TRUE, prob = c(30,70)),
           bin3 = sample(c(0,1), 20, replace=TRUE, prob = c(30,70)))
a

## Mutate the individuals with a low percentage
aMut <- mutation(a, 0.1, NULL)
## Check which values are not like the originals
a == aMut

## Mutate the individuals with a high percentage
aMut <- mutation(a, 0.4, NULL)
## Check which values are not like the originals
a == aMut

windfarmGA documentation built on May 5, 2021, 5:08 p.m.