swap_mutation: Swap mutation of turbine layouts

In windfarmGA: Genetic Algorithm for Wind Farm Layout Optimization

Swap mutation of turbine layouts

Description

Replace occupied grid cells with unused ones. The number of swaps is max(min_swaps, Binomial(n, p)), so each individual explores at least min_swaps new cells (default 1). The number of turbines stays n.

Usage

swap_mutation(ids, grid_ids, p, seed = NULL, min_swaps = NULL, visit = NULL)

Arguments

ids	Integer matrix with n rows (turbines) and one column per individual
grid_ids	All valid grid cell IDs
p	Mutation probability per turbine
seed	Set a seed for comparability. Default is NULL
min_swaps	Minimum number of swaps per individual. Default is getOption("windfarmGA.min_swaps") (1)
visit	Named visit counts per grid ID. Free cells with fewer visits are more likely to be chosen. Default is NULL (uniform)

Value

Integer matrix of unique grid IDs, same dimension as ids

See Also

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

Examples

ids <- cbind(c(1, 3, 5, 7), c(2, 4, 6, 8))
swap_mutation(ids, grid_ids = 1:20, p = 0.5, seed = 1)

windfarmGA documentation built on Sept. 14, 2026, 9:08 a.m.