pal.math
Class GeneralizedDEOptimizer
java.lang.Object
pal.math.MultivariateMinimum
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
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 java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
GeneralizedDEOptimizer
public GeneralizedDEOptimizer()
GeneralizedDEOptimizer
public GeneralizedDEOptimizer(int populationSize)
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 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
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 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)
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