mutation: Mutation Method

In windfarmGA: Genetic Algorithm for Wind Farm Layout Optimization

Mutation Method

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()

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 April 4, 2025, 3:39 a.m.