net.sourceforge.cilib.pso
Class PSO

java.lang.Object
  net.sourceforge.cilib.algorithm.Algorithm
      net.sourceforge.cilib.algorithm.population.PopulationBasedAlgorithm
          net.sourceforge.cilib.algorithm.population.SinglePopulationBasedAlgorithm
              net.sourceforge.cilib.pso.PSO

All Implemented Interfaces:

Serializable, Runnable, ParticipatingAlgorithm, Cloneable

Direct Known Subclasses:

LFPSO, RNAPSO

public class PSO
extends SinglePopulationBasedAlgorithm
implements ParticipatingAlgorithm

An implementation of the standard PSO algorithm.

References:

• J. Kennedy and R.C. Eberhart, "Particle swarm optimization," in Proceedings of IEEE International Conference on Neural Networks, vol. IV, (Perth Australia), pp. 1942-1948, 1995.
• R.C. Eberhart and J. Kennedy, "A new optimizer using particle swarm theory," in Proceedings of the Sixth International Symposium on Micro Machine and Human Science, (Nagoya, Japan), pp. 39-43, 1995.
• Y. Shi amd R.C. Eberhart, "A modified particle swarm optimizer," in Proceedings of the IEEE Congress on Evolutionary Computation, (Anchorage, Alaska), pp. 69-73, May 1998.

Author:

Edwin Peer, Gary Pampara

See Also:

Serialized Form

Field Summary

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

initialisationStrategy

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

optimisationProblem

Constructor Summary

PSO()
Creates a new instance of PSO.

PSO(PSO copy)
Create a copy of the provided instance.

Method Summary

protected void	algorithmIteration() Perform the iteration of the PSO algorithm, use the appropriate IterationStrategy to perform the iteration.
OptimisationSolution	getBestSolution() Get the best current solution.
PSO	getClone() Create a cloned copy of the current object and return it.
Particle	getContribution() Returns contribution to the solution for the co-operative optimisation algorithm.
Fitness	getContributionFitness() Returns the fitness of contribution to the solution.
IterationStrategy<PSO>	getIterationStrategy() Get the IterationStrategy of the PSO algorithm.
List<OptimisationSolution>	getSolutions() Get the collection of best solutions.
Topology<Particle>	getTopology() Accessor for the topology being used.
void	performInitialisation() Perform the required initialisation for the algorithm.
void	reset() Reset the Algorithm internals if needed.
void	setIterationStrategy(IterationStrategy<PSO> iterationStrategy) Set the IterationStrategy to be used.
void	setTopology(Topology topology) Sets the particle topology used.
void	updateContributionFitness(Fitness fitness) Updates the new fitness for the solution contribution.

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

accept, getInitialisationStrategy, setInitialisationStrategy

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

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

Methods inherited from class java.lang.Object

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

Constructor Detail

PSO

public PSO()

Creates a new instance of PSO. All fields are initialised to reasonable defaults. Note that the OptimisationProblem is initially null and must be set before Algorithm.initialise() is called.

PSO

public PSO(PSO copy)

Create a copy of the provided instance.

Parameters:

copy - The instance to copy.

Method Detail

getClone

public PSO getClone()

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 SinglePopulationBasedAlgorithm

Returns:

An exact clone of the current object instance.

See Also:

Object.clone()

reset

public void reset()

Reset the Algorithm internals if needed.

Overrides:

reset in class Algorithm

performInitialisation

public void performInitialisation()

Perform the required initialisation for the algorithm. Create the particles and add then to the specified topology.

Overrides:

performInitialisation in class Algorithm

algorithmIteration

protected void algorithmIteration()

Perform the iteration of the PSO algorithm, use the appropriate IterationStrategy to perform the iteration.

Specified by:

algorithmIteration in class SinglePopulationBasedAlgorithm

getBestSolution

public OptimisationSolution getBestSolution()

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()

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

Specified by:

getSolutions in class PopulationBasedAlgorithm

Returns:

The Collection<OptimisationSolution> containing the solutions.

setTopology

public void setTopology(Topology topology)

Sets the particle topology used. The default is GBestTopology.

Specified by:

setTopology in class SinglePopulationBasedAlgorithm

Parameters:

topology - A class that implements the Topology interface.

getTopology

public Topology<Particle> getTopology()

Accessor for the topology being used.

Specified by:

getTopology in class SinglePopulationBasedAlgorithm

Returns:

The Topology being used.

getContribution

public Particle 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()

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)

Updates the new fitness for the solution contribution.

Specified by:

updateContributionFitness in interface ParticipatingAlgorithm

Parameters:

fitness - The new fitness of the contribution.

getIterationStrategy

public IterationStrategy<PSO> getIterationStrategy()

Get the IterationStrategy of the PSO algorithm.

Returns:

Returns the iterationStrategy..

setIterationStrategy

public void setIterationStrategy(IterationStrategy<PSO> iterationStrategy)

Set the IterationStrategy to be used.

Parameters:

iterationStrategy - The iterationStrategy to set.