pal.math
Class GeneralizedDEOptimizer

java.lang.Object
  extended by pal.math.MultivariateMinimum
      extended by pal.math.GeneralizedDEOptimizer

public class GeneralizedDEOptimizer
extends MultivariateMinimum

Provides an general interface to the DifferentialEvolution class that is not tied to a certain number of parameters (as DifferentialEvolution is). Works but creating a new DiffentialEvolution engine when presented with a new number of parameters. All the actual optimisation work is handled by DifferentialEvolution.,

Version:
$Id: GeneralizedDEOptimizer.java,v 1.8 2003/05/30 08:51:10 matt Exp $
Author:
Matthew Goode

Nested Class Summary
 
Nested classes/interfaces inherited from class pal.math.MultivariateMinimum
MultivariateMinimum.Factory
 
Field Summary
 
Fields inherited from class pal.math.MultivariateMinimum
maxFun, numFun, numFuncStops
 
Constructor Summary
GeneralizedDEOptimizer()
           
GeneralizedDEOptimizer(int populationSize)
           
 
Method Summary
static MultivariateMinimum.Factory generateFactory()
          Generate a MultivariateMinimum.Factory for an GeneralizedDEOptimiser with a population size proportional to the size of the problem
static MultivariateMinimum.Factory generateFactory(int populationSize)
          Generate a MultivariateMinimum.Factory for an GeneralizedDEOptimiser with a set population size
 void optimize(MultivariateFunction f, double[] xvec, double tolfx, double tolx)
          The actual optimization routine It finds a minimum close to vector x when the absolute tolerance for each parameter is specified.
 void optimize(MultivariateFunction f, double[] xvec, double tolfx, double tolx, MinimiserMonitor monitor)
          The actual optimization routine It finds a minimum close to vector x when the absolute tolerance for each parameter is specified.
 
Methods inherited from class pal.math.MultivariateMinimum
copy, findMinimum, findMinimum, findMinimum, stopCondition
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Constructor Detail

GeneralizedDEOptimizer

public GeneralizedDEOptimizer()

GeneralizedDEOptimizer

public GeneralizedDEOptimizer(int populationSize)
Method Detail

optimize

public void optimize(MultivariateFunction f,
                     double[] xvec,
                     double tolfx,
                     double tolx)
The actual optimization routine It finds a minimum close to vector x when the absolute tolerance for each parameter is specified.

Specified by:
optimize in class 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

optimize

public void optimize(MultivariateFunction f,
                     double[] xvec,
                     double tolfx,
                     double tolx,
                     MinimiserMonitor monitor)
The actual optimization routine It finds a minimum close to vector x when the absolute tolerance for each parameter is specified.

Overrides:
optimize in class 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
monitor - A monitor object that receives information about the minimising process (for display purposes)

generateFactory

public static final MultivariateMinimum.Factory generateFactory(int populationSize)
Generate a MultivariateMinimum.Factory for an GeneralizedDEOptimiser with a set population size

Parameters:
populationSize - The set population size

generateFactory

public static final MultivariateMinimum.Factory generateFactory()
Generate a MultivariateMinimum.Factory for an GeneralizedDEOptimiser with a population size proportional to the size of the problem