Package pal.math
Class GeneralizedDEOptimizer
- java.lang.Object
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- pal.math.MultivariateMinimum
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- pal.math.GeneralizedDEOptimizer
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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
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Nested Class Summary
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Nested classes/interfaces inherited from class pal.math.MultivariateMinimum
MultivariateMinimum.Factory
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Field Summary
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Fields inherited from class pal.math.MultivariateMinimum
maxFun, numFun, numFuncStops
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Constructor Summary
Constructors Constructor Description GeneralizedDEOptimizer()
GeneralizedDEOptimizer(int populationSize)
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Method Summary
All Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method Description static MultivariateMinimum.Factory
generateFactory()
Generate a MultivariateMinimum.Factory for an GeneralizedDEOptimiser with a population size proportional to the size of the problemstatic MultivariateMinimum.Factory
generateFactory(int populationSize)
Generate a MultivariateMinimum.Factory for an GeneralizedDEOptimiser with a set population sizevoid
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
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Method Detail
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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 classMultivariateMinimum
- 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
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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 classMultivariateMinimum
- 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 parametermonitor
- A monitor object that receives information about the minimising process (for display purposes)
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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
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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
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