landscapeGeneratorUNI: Unimodal Fitness Landscape

In CEGO: Combinatorial Efficient Global Optimization

Description

This function generates uni-modal fitness landscapes based on distance measures. The fitness is the distance to a reference individual or center. Hence, the reference individual is the optimum of the landscape. This function is essentially a wrapper for the landscapeGeneratorMUL

Usage

landscapeGeneratorUNI(ref, distanceFunction)

Arguments

ref	reference individual
distanceFunction	Distance function, used to evaluate d(x,ref), 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.

References

Moraglio, Alberto, Yong-Hyuk Kim, and Yourim Yoon. "Geometric surrogate-based optimisation for permutation-based problems." Proceedings of the 13th annual conference companion on Genetic and evolutionary computation. ACM, 2011.

See Also

landscapeGeneratorMUL, landscapeGeneratorGaussian

Examples

fun <- landscapeGeneratorUNI(ref=1:7,distancePermutationCos)
## for single solutions, note that the function still requires list input:
x <- 1:7
fun(list(x))
x <- 7:1
fun(list(x))
x <- sample(7)
fun(list(x))
## multiple solutions at once:
x <- replicate(5,sample(7),FALSE)
fun(x)

CEGO documentation built on May 14, 2021, 1:08 a.m.