Description Usage Arguments Value Examples
Create a list with cmaes_gen class. Basically, the function transform the population into a class that is accepted by the MOCMAES and SMOCMAES function.
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population |
The number of objective functions. A scalar value. |
ps_target |
The target success rate. Used to initialize cmaes_gen$averageSuccessRate. |
stepSize |
The initial step size. |
evoPath |
A vector of numbers indicating evolution path of each variable. |
covarianceMatrix |
Covariance matrix of the variables. |
An object of cmaes_gen class. It can be used as MO-CMA-ES parent. It is a 5 tuple: x (the design point, length = number of variable),averageSuccessRate (scalar),stepSize (scalar), evoPath (evolution path, vector, length = number of variable ),covarianceMatrix (square matrix with ncol = nrow = number of variable).
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | nVar <- 14
nObjective <- 5
nIndividual <- 100
crossoverProbability <- 1
ps_target <- 1 / (5 + ( 1 / 2 )^0.5 )
pop <- matrix(stats::runif(nIndividual*nVar), nrow = nVar) # create the population
a_list <- cmaes_gen(pop)
control <- list(successProbTarget=ps_target,crossoverProbability=crossoverProbability)
# run a generation of MO-CMA-ES with standard WFG8 test function.
numpyready <- reticulate::py_module_available('numpy')
pygmoready <- reticulate::py_module_available('pygmo')
py_module_ready <- numpyready && pygmoready
if(py_module_ready) # prevent error on testing the example
newGeneration <- MOCMAES(a_list,nObjective,WFG8,control,nObjective)
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