iterator
Class AbstractPopulationOptimizer<T extends BoundConstrainedProblem>

java.lang.Object
  iterator.AbstractIterator
      iterator.AbstractOptimizer<T>
          iterator.AbstractInitialSampleBasedOptimizer<T>
              iterator.AbstractPopulationOptimizer<T>

Type Parameters:

T - the type of OptimizationProblem being solved.

All Implemented Interfaces:

DataListener, InitialSamplesSettable, Iterable, LoggableIterator, RepeatableLoggableIterator

Direct Known Subclasses:

BasicRealEncodedGA, ISIS

public abstract class AbstractPopulationOptimizer<T extends BoundConstrainedProblem>
extends AbstractInitialSampleBasedOptimizer<T>

Optimization algorithm that evaluates an entire population at each iteration.

Author:

dgorur

Field Summary

protected double	currentBestG
protected double	lastBestG
protected DataBlock	nextBlock

Fields inherited from class iterator.AbstractInitialSampleBasedOptimizer

uniform

Fields inherited from class iterator.AbstractOptimizer

doubleFormat, funEvalCount, logWriter

Fields inherited from class iterator.AbstractIterator

diagnosticString, iter

Constructor Summary

AbstractPopulationOptimizer()

Method Summary

protected abstract cern.colt.matrix.DoubleMatrix2D	computeNextPoints() Computes the next set of candidate solutions.
protected void	evaluatePoints(cern.colt.matrix.DoubleMatrix2D nextPoints) Evaluates the objective (and constraints) given set of points.
int	getPopulationSize() Returns the population size.
void	init() Initialization routine
void	setInitialSamples(DataBlock block) Sets the given block of samples as the set of initial samples.
void	setInitialSamples(cern.colt.matrix.DoubleMatrix2D initialSamples)
void	setInitialSamples(cern.colt.matrix.DoubleMatrix2D x, cern.colt.matrix.DoubleMatrix2D y) Sets the initial samples as per the given inputs and outputs.
void	setPopulationSize(int populationSize) Sets the population size.
void	singleIteration() Performs a single iteration.

Methods inherited from class iterator.AbstractInitialSampleBasedOptimizer

getRandomSeed, makeInitialSamples, setRandomSeed

Methods inherited from class iterator.AbstractOptimizer

clear, dataAdded, dataAdded, dataRemoved, dataRemoved, getDataHandler, getFunEvalCount, getLogFileName, getMaxFunEval, getProblem, isTerminated, iterate, setDataHandler, setFunEvalCount, setLogFileName, setMaxFunEval, setProblem, updateDiagnostics, writeInitialRunLog

Methods inherited from class iterator.AbstractIterator

isVerbose, printDiagnostics, setVerbose

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface iterator.LoggableIterator

getLogFileName, setLogFileName

Methods inherited from interface iterator.Iterable

isTerminated, iterate

Field Detail

currentBestG

protected double currentBestG

lastBestG

protected double lastBestG

nextBlock

protected DataBlock nextBlock

Constructor Detail

AbstractPopulationOptimizer

public AbstractPopulationOptimizer()

Method Detail

getPopulationSize

public int getPopulationSize()

Returns the population size.

Returns:

the population size.

init

public void init()

Description copied from interface: Iterable

Initialization routine

Specified by:

init in interface Iterable

Overrides:

init in class AbstractInitialSampleBasedOptimizer<T extends BoundConstrainedProblem>

setInitialSamples

public void setInitialSamples(DataBlock block)

Description copied from interface: InitialSamplesSettable

Sets the given block of samples as the set of initial samples. Note: this block contains inputs and outputs.

Parameters:

block - the given DataBlock.

setInitialSamples

public void setInitialSamples(cern.colt.matrix.DoubleMatrix2D initialSamples)

Parameters:

initialSamples - initial matrix of points, stored row-wise.

setInitialSamples

public void setInitialSamples(cern.colt.matrix.DoubleMatrix2D x,
                              cern.colt.matrix.DoubleMatrix2D y)

Description copied from interface: InitialSamplesSettable

Sets the initial samples as per the given inputs and outputs.

Parameters:

x - the given set of inputs.

y - the given set of outputs.

setPopulationSize

public void setPopulationSize(int populationSize)

Sets the population size.

Parameters:

populationSize - the given population size.

singleIteration

public void singleIteration()

Description copied from interface: Iterable

Performs a single iteration.

computeNextPoints

protected abstract cern.colt.matrix.DoubleMatrix2D computeNextPoints()

Computes the next set of candidate solutions.

Returns:

a DoubleMatrix2D containing design points row-wise.

evaluatePoints

protected void evaluatePoints(cern.colt.matrix.DoubleMatrix2D nextPoints)

Evaluates the objective (and constraints) given set of points.

Parameters:

nextPoints - the given set of inputs, row-wise.