edaOptimize {copulaedas} | R Documentation |
Local Optimization Methods
Description
Methods for the edaOptimize
generic function.
Usage
edaOptimizeDisabled(eda, gen, pop, popEval, f, lower, upper)
Arguments
eda |
|
gen |
Generation. |
pop |
Matrix with one row for each solution in the population. |
popEval |
Vector with the evaluation of each solution in |
f |
Objective function. |
lower |
Lower bounds of the variables of the objective function. |
upper |
Upper bounds of the variables of the objective function. |
Details
Local optimization methods improve the solutions sampled by the search distribution. These methods can also be used to implement repairing strategies for constrained problems in which the simulated solutions may be unfeasible and some strategy to repair these solutions is available.
The following local optimization methods are implemented.
edaOptimizeDisabled
Disable local optimization. This is the default method of the
edaOptimize
generic function.
Value
A list
with the following components.
pop |
Matrix with one row for each solution in the optimized population. |
popEval |
Vector with the evaluation of each solution in |
References
Gonzalez-Fernandez Y, Soto M (2014). copulaedas: An R Package for Estimation of Distribution Algorithms Based on Copulas. Journal of Statistical Software, 58(9), 1-34. http://www.jstatsoft.org/v58/i09/.