pal.math
Class DifferentialEvolution

java.lang.Object
  |
  +--pal.math.MultivariateMinimum
        |
        +--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)
 
Fields inherited from class pal.math.MultivariateMinimum
maxFun, numFun, numFuncStops
 
Constructor Summary
DifferentialEvolution(int dim)
          construct DE optimization modul (population size is selected automatically) DE web page: http://www.icsi.berkeley.edu/~storn/code.html
DifferentialEvolution(int dim, int popSize)
          construct optimization modul
 
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).
 
Methods inherited from class pal.math.MultivariateMinimum
copy, findMinimum, findMinimum, stopCondition
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Field Detail

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)
Constructor Detail

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 vector
popSize - population size
Method Detail

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 function
xvec - initial guesses for the minimum (contains the location of the minimum on return)
tolfx - absolute tolerance of function value
tolx - absolute tolerance of each parameter