optimRS: Combinatorial Random Search

In CEGO: Combinatorial Efficient Global Optimization

Combinatorial Random Search

Description

Random Search for mixed or combinatorial optimization. Solutions are generated completely at random.

Usage

optimRS(x = NULL, fun, control = list())

Arguments

x	Optional set of solution(s) as a list, which are added to the randomly generated solutions and are also evaluated with the target function.
fun	target function to be minimized
control	(list), with the options: budget The limit on number of target function evaluations (stopping criterion) (default: 100) vectorized Boolean. Defines whether target function is vectorized (takes a list of solutions as argument) or not (takes single solution as argument). Default: FALSE creationFunction Function to create individuals/solutions in search space. Default is a function that creates random permutations of length 6

Value

a list:

xbest

best solution found

ybest

fitness of the best solution

x

history of all evaluated solutions

y

corresponding target function values f(x)

count

number of performed target function evaluations

See Also

optimCEGO, optimEA, optim2Opt, optimMaxMinDist

Examples

seed=0
#distance
dF <- distancePermutationHamming
#creation
cF <- function()sample(5)
#objective function
lF <- landscapeGeneratorUNI(1:5,dF)
#start optimization
set.seed(seed)
res <- optimRS(,lF,list(creationFunction=cF,budget=100,
	vectorized=TRUE)) ##target function is "vectorized", expects list as input
res$xbest 

CEGO documentation built on April 3, 2025, 7:48 p.m.