net.sourceforge.cilib.cooperative
Class SplitCooperativeAlgorithm

java.lang.Object
  net.sourceforge.cilib.algorithm.Algorithm
      net.sourceforge.cilib.algorithm.population.PopulationBasedAlgorithm
          net.sourceforge.cilib.algorithm.population.MultiPopulationBasedAlgorithm
              net.sourceforge.cilib.cooperative.SplitCooperativeAlgorithm

All Implemented Interfaces:

Serializable, Iterable<PopulationBasedAlgorithm>, Runnable, ParticipatingAlgorithm, Cloneable

public class SplitCooperativeAlgorithm
extends MultiPopulationBasedAlgorithm
implements ParticipatingAlgorithm

TODO test this class This class forms that basis for any co-operative optimisation implementations. Any algorithm that wishes to participate in a co-operative optimisation algorithm must implement the ParticipatingAlgorithm interface. This class also implements ParticipatingAlgorithm meaning that co-operative algorithms can be composed of co-operative algorithms again.

Author:

Edwin Peer, Theuns Cloete

See Also:

Serialized Form

Field Summary

protected CooperativeEntity	context
protected ContributionUpdateStrategy	contributionUpdateStrategy
protected FitnessUpdateStrategy	fitnessUpdateStrategy
protected SplitStrategy	splitStrategy

Fields inherited from class net.sourceforge.cilib.algorithm.population.MultiPopulationBasedAlgorithm

algorithmIterator, subPopulationsAlgorithms

Fields inherited from class net.sourceforge.cilib.algorithm.Algorithm

optimisationProblem

Constructor Summary

SplitCooperativeAlgorithm()
Creates a new instance of a SplitCooperativeAglorithm.

SplitCooperativeAlgorithm(SplitCooperativeAlgorithm copy)

Method Summary

void	addPopulationBasedAlgorithm(PopulationBasedAlgorithm algorithm) Add a PopulationBasedAlgorithm to the list of maintained sub-populations.
void	algorithmIteration() The actual operations that the current Algorithm performs within a single iteration.
OptimisationSolution	getBestSolution() Get the best current solution.
SplitCooperativeAlgorithm	getClone() Create a cloned copy of the current object and return it.
CooperativeEntity	getContext()
Entity	getContribution() Returns contribution to the solution for the co-operative optimisation algorithm.
Fitness	getContributionFitness() Returns the fitness of contribution to the solution.
ContributionUpdateStrategy	getContributionUpdateStrategy()
FitnessUpdateStrategy	getFitnessUpdateStrategy()
int	getNumberOfParticipants()
List<OptimisationSolution>	getSolutions() Get the collection of best solutions.
SplitStrategy	getSplitStrategy()
void	performInitialisation() Perform the needed initialisation required before the execution of the algorithm starts.
void	performUninitialisation() Perform the needed unintialisation steps after the algorithm completes it's execution.
void	reset() Reset the Algorithm internals if needed.
void	setContext(CooperativeEntity c)
void	setContributionUpdateStrategy(ContributionUpdateStrategy contributionUpdate)
void	setFitnessUpdateStrategy(FitnessUpdateStrategy fitnessUpdate)
void	setSplitStrategy(SplitStrategy split)
void	updateContributionFitness(Fitness fitness) The purpose of this method should not be confused with the ContributionUpdateStrategy.

Methods inherited from class net.sourceforge.cilib.algorithm.population.MultiPopulationBasedAlgorithm

accept, getAlgorithmIterator, getInitialisationStrategy, getPopulations, getTopology, iterator, removePopulationBasedalgorithm, setAlgorithmIterator, setInitialisationStrategy, setPopulations

Methods inherited from class net.sourceforge.cilib.algorithm.Algorithm

addAlgorithmListener, addStoppingCondition, get, getAlgorithmList, getIterations, getOptimisationProblem, getPercentageComplete, getStoppingConditions, initialise, isFinished, performIteration, removeAlgorithmListener, removeStoppingCondition, run, setOptimisationProblem, terminate

Methods inherited from class java.lang.Object

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

Field Detail

context

protected CooperativeEntity context

splitStrategy

protected SplitStrategy splitStrategy

fitnessUpdateStrategy

protected FitnessUpdateStrategy fitnessUpdateStrategy

contributionUpdateStrategy

protected ContributionUpdateStrategy contributionUpdateStrategy

Constructor Detail

SplitCooperativeAlgorithm

public SplitCooperativeAlgorithm()

Creates a new instance of a SplitCooperativeAglorithm.

SplitCooperativeAlgorithm

public SplitCooperativeAlgorithm(SplitCooperativeAlgorithm copy)

Method Detail

getClone

public SplitCooperativeAlgorithm getClone()

Description copied from class: PopulationBasedAlgorithm

Create a cloned copy of the current object and return it. In general the created copy will be a deep copy of the provided instance. As a result this operation an be quite expensive if used incorrectly.

Specified by:

getClone in interface Cloneable

Specified by:

getClone in class PopulationBasedAlgorithm

Returns:

An exact clone of the current object instance.

See Also:

Object.clone()

reset

public void reset()

Description copied from class: MultiPopulationBasedAlgorithm

Reset the Algorithm internals if needed.

Overrides:

reset in class MultiPopulationBasedAlgorithm

getBestSolution

public OptimisationSolution getBestSolution()

Description copied from class: PopulationBasedAlgorithm

Get the best current solution. This best solution is determined from the personal bests of the particles.

Specified by:

getBestSolution in class PopulationBasedAlgorithm

Returns:

The OptimisationSolution representing the best solution.

getSolutions

public List<OptimisationSolution> getSolutions()

Description copied from class: PopulationBasedAlgorithm

Get the collection of best solutions. This result does not actually make sense in the normal PSO algorithm, but rather in a MultiObjective optimization.

Specified by:

getSolutions in class PopulationBasedAlgorithm

Returns:

The Collection<OptimisationSolution> containing the solutions.

getContext

public CooperativeEntity getContext()

setContext

public void setContext(CooperativeEntity c)

addPopulationBasedAlgorithm

public void addPopulationBasedAlgorithm(PopulationBasedAlgorithm algorithm)

Description copied from class: MultiPopulationBasedAlgorithm

Add a PopulationBasedAlgorithm to the list of maintained sub-populations.

Overrides:

addPopulationBasedAlgorithm in class MultiPopulationBasedAlgorithm

Parameters:

algorithm - The PopulationBasedAlgorithm to add to the current collection.

getNumberOfParticipants

public int getNumberOfParticipants()

getSplitStrategy

public SplitStrategy getSplitStrategy()

setSplitStrategy

public void setSplitStrategy(SplitStrategy split)

getContributionUpdateStrategy

public ContributionUpdateStrategy getContributionUpdateStrategy()

setContributionUpdateStrategy

public void setContributionUpdateStrategy(ContributionUpdateStrategy contributionUpdate)

getContribution

public Entity getContribution()

Description copied from interface: ParticipatingAlgorithm

Returns contribution to the solution for the co-operative optimisation algorithm.

Specified by:

getContribution in interface ParticipatingAlgorithm

Returns:

The algorithm's solution contribution.

getContributionFitness

public Fitness getContributionFitness()

Description copied from interface: ParticipatingAlgorithm

Returns the fitness of contribution to the solution.

Specified by:

getContributionFitness in interface ParticipatingAlgorithm

Returns:

The fitness of the solution contribution.

updateContributionFitness

public void updateContributionFitness(Fitness fitness)

The purpose of this method should not be confused with the ContributionUpdateStrategy. This method sets the fitness for the context of the cooperating algorithm, i.e. the fitness for all cooperating algorithms as a whole.

Specified by:

updateContributionFitness in interface ParticipatingAlgorithm

Parameters:

fitness - The new fitness of the contribution.

getFitnessUpdateStrategy

public FitnessUpdateStrategy getFitnessUpdateStrategy()

setFitnessUpdateStrategy

public void setFitnessUpdateStrategy(FitnessUpdateStrategy fitnessUpdate)

performInitialisation

public void performInitialisation()

Description copied from class: Algorithm

Perform the needed initialisation required before the execution of the algorithm starts.

Overrides:

performInitialisation in class Algorithm

performUninitialisation

public void performUninitialisation()

Description copied from class: Algorithm

Perform the needed unintialisation steps after the algorithm completes it's execution.

Overrides:

performUninitialisation in class Algorithm

algorithmIteration

public void algorithmIteration()

Description copied from class: MultiPopulationBasedAlgorithm

The actual operations that the current Algorithm performs within a single iteration.

Specified by:

algorithmIteration in class MultiPopulationBasedAlgorithm