public class DifferentialEvolution extends MultivariateMinimum
| Modifier and Type | Field and Description |
|---|---|
double |
CR
Crossing over factor (default 0.9)
|
double |
F
weight factor (default 0.7)
|
int |
prin
variable controlling print out, default value = 0
(0 = no output, 1 = print final value,
2 = detailed map of optimization process)
|
maxFun, numFun, numFuncStops| Constructor and Description |
|---|
DifferentialEvolution(int dim)
construct DE optimization modul (population size is
selected automatically)
|
DifferentialEvolution(int dim,
int popSize)
construct optimization modul
|
| Modifier and Type | Method and Description |
|---|---|
void |
optimize(MultivariateFunction func,
double[] xvec,
double tolfx,
double tolx)
The actual optimization routine
(needs to be implemented in a subclass of MultivariateMinimum).
|
copy, findMinimum, findMinimum, stopConditionpublic double F
public double CR
public int prin
public DifferentialEvolution(int dim)
DE web page: http://www.icsi.berkeley.edu/~storn/code.html
dim - dimension of optimization vectorpublic DifferentialEvolution(int dim,
int popSize)
dim - dimension of optimization vectorpopSize - population sizepublic void optimize(MultivariateFunction func, double[] xvec, double tolfx, double tolx)
MultivariateMinimumoptimize in class MultivariateMinimumfunc - multivariate functionxvec - initial guesses for the minimum
(contains the location of the minimum on return)tolfx - absolute tolerance of function valuetolx - absolute tolerance of each parameterCopyright © 2015–2021 Fiji. All rights reserved.