landscapeGeneratorMUL: Multimodal Fitness Landscape

In CEGO: Combinatorial Efficient Global Optimization

Multimodal Fitness Landscape

Description

This function generates multi-modal fitness landscapes based on distance measures. The fitness is the minimal distance to several reference individuals or centers. Hence, each reference individual is an optimum of the landscape.

Usage

landscapeGeneratorMUL(ref, distanceFunction)

Arguments

ref	list of reference individuals / centers
distanceFunction	Distance function, used to evaluate d(x,ref[[n]]), where x is an arbitrary new individual

Value

returns a function. The function requires a list of candidate solutions as its input, where each solution is suitable for use with the distance function. The function returns a numeric vector.

See Also

landscapeGeneratorUNI, landscapeGeneratorGaussian

Examples

fun <- landscapeGeneratorMUL(ref=list(1:7,c(2,4,1,5,3,7,6)),distancePermutationCos)
x <- 1:7
fun(list(x))
x <- c(2,4,1,5,3,7,6)
fun(list(x))
x <- 7:1
fun(list(x))
x <- sample(7)
fun(list(x))
## multiple solutions at once:
x <- append(list(1:7,c(2,4,1,5,3,7,6)),replicate(5,sample(7),FALSE))
fun(x)

CEGO documentation built on May 29, 2024, 3:35 a.m.