pal.math
Class DifferentialEvolution
java.lang.Object
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+--pal.math.MultivariateMinimum
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+--pal.math.DifferentialEvolution
- public class DifferentialEvolution
- extends MultivariateMinimum
global minimization of a real-valued function of several
variables without using derivatives using a genetic algorithm
(Differential Evolution)
Field Summary |
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) |
Method Summary |
void |
optimize(MultivariateFunction func,
double[] xvec,
double tolfx,
double tolx)
The actual optimization routine
(needs to be implemented in a subclass of MultivariateMinimum).
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Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
F
public double F
- weight factor (default 0.7)
CR
public double CR
- Crossing over factor (default 0.9)
prin
public int prin
- variable controlling print out, default value = 0
(0 -> no output, 1 -> print final value,
2 -> detailed map of optimization process)
DifferentialEvolution
public DifferentialEvolution(int dim)
- construct DE optimization modul (population size is
selected automatically)
DE web page:
http://www.icsi.berkeley.edu/~storn/code.html
- Parameters:
dim
- dimension of optimization vector
DifferentialEvolution
public DifferentialEvolution(int dim,
int popSize)
- construct optimization modul
- Parameters:
dim
- dimension of optimization vectorpopSize
- population size
optimize
public void optimize(MultivariateFunction func,
double[] xvec,
double tolfx,
double tolx)
- Description copied from class:
MultivariateMinimum
- The actual optimization routine
(needs to be implemented in a subclass of MultivariateMinimum).
It finds a minimum close to vector x when the
absolute tolerance for each parameter is specified.
- Overrides:
optimize
in class MultivariateMinimum
- Following copied from class:
pal.math.MultivariateMinimum
- Parameters:
f
- 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 parameter