CEGO (version 2.1.0)

optimMaxMinDist: Max-Min-Distance Optimizer

Description

One-shot optimizer: Create a design with maximum sum of distances, and evaluate. Best candidate is returned.

Usage

optimMaxMinDist(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. designBudget budget of the design function designMaxMinDist, which is the number of randomly created candidates in each iteration.

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, optimRS, optim2Opt

Examples

# NOT RUN {
seed=0
#distance
dF <- distancePermutationHamming
#creation
cF <- function()sample(5)
#objective function
lF <- landscapeGeneratorUNI(1:5,dF)
#start optimization
set.seed(seed)
res <- optimMaxMinDist(,lF,list(creationFunction=cF,budget=20,
	vectorized=TRUE)) ##target function is "vectorized", expects list as input
res$xbest 

# }