#include <itkParticleSwarmOptimizerBase.h>

Inheritance diagram for itk::ParticleSwarmOptimizerBase:

Collaboration diagram for itk::ParticleSwarmOptimizerBase:

Classes
struct	ParticleData
Public Types
typedef SmartPointer< const Self >	ConstPointer
typedef CostFunctionType::MeasureType	MeasureType
typedef unsigned int	NumberOfGenerationsType
typedef unsigned int	NumberOfIterationsType
typedef unsigned int	NumberOfParticlesType
typedef std::vector< std::pair < ParametersType::ValueType, ParametersType::ValueType > >	ParameterBoundsType
typedef SmartPointer< Self >	Pointer
typedef Statistics::MersenneTwisterRandomVariateGenerator	RandomVariateGeneratorType
typedef ParticleSwarmOptimizerBase	Self
typedef SingleValuedNonLinearOptimizer	Superclass
typedef std::vector< ParticleData >	SwarmType
typedef ParametersType::ValueType	ValueType
Public Member Functions
virtual MeasureType	GetFunctionConvergenceTolerance ()
virtual bool	GetInitializeNormalDistribution ()
virtual NumberOfIterationsType	GetMaximalNumberOfIterations ()
virtual const char *	GetNameOfClass () const
virtual NumberOfGenerationsType	GetNumberOfGenerationsWithMinimalImprovement ()
virtual NumberOfParticlesType	GetNumberOfParticles ()
ParameterBoundsType	GetParameterBounds () const
virtual ParametersType	GetParametersConvergenceTolerance ()
virtual double	GetPercentageParticlesConverged ()
virtual bool	GetPrintSwarm ()
virtual RandomVariateGeneratorType::IntegerType	GetSeed ()
virtual const std::string	GetStopConditionDescription () const
virtual bool	GetUseSeed ()
MeasureType	GetValue () const
virtual void	InitializeNormalDistributionOff ()
virtual void	InitializeNormalDistributionOn ()
void	PrintSwarm (std::ostream &os, Indent indent) const
virtual void	PrintSwarmOff ()
virtual void	PrintSwarmOn ()
virtual void	SetFunctionConvergenceTolerance (MeasureType _arg)
virtual void	SetInitializeNormalDistribution (bool _arg)
virtual void	SetMaximalNumberOfIterations (NumberOfIterationsType _arg)
virtual void	SetNumberOfGenerationsWithMinimalImprovement (NumberOfGenerationsType _arg)
void	SetNumberOfParticles (NumberOfParticlesType n)
void	SetParametersConvergenceTolerance (ValueType convergenceTolerance, unsigned int sz)
virtual void	SetParametersConvergenceTolerance (ParametersType _arg)
virtual void	SetPercentageParticlesConverged (double _arg)
virtual void	SetPrintSwarm (bool _arg)
virtual void	SetSeed (RandomVariateGeneratorType::IntegerType _arg)
virtual void	SetUseSeed (bool _arg)
void	StartOptimization (void)
virtual void	UseSeedOff ()
virtual void	UseSeedOn ()

void	SetInitialSwarm (const SwarmType &initialSwarm)
void	ClearSwarm ()

virtual void	SetParameterBounds (ParameterBoundsType &bounds)
void	SetParameterBounds (std::pair< ParametersType::ValueType, ParametersType::ValueType > &bounds, unsigned int n)
Protected Member Functions
void	FileInitialization ()
virtual void	Initialize ()
void	operator= (const Self &)
	ParticleSwarmOptimizerBase ()
	ParticleSwarmOptimizerBase (const Self &)
void	PrintParamtersType (const ParametersType &x, std::ostream &os) const
void	PrintSelf (std::ostream &os, Indent indent) const
void	RandomInitialization ()
virtual void	UpdateSwarm ()=0
virtual void	ValidateSettings ()
virtual	~ParticleSwarmOptimizerBase ()
Protected Attributes
CostFunctionType::MeasureType	m_FunctionBestValue
std::vector< MeasureType >	m_FunctionBestValueMemory
CostFunctionType::MeasureType	m_FunctionConvergenceTolerance
bool	m_InitializeNormalDistribution
NumberOfIterationsType	m_IterationIndex
NumberOfIterationsType	m_MaximalNumberOfIterations
NumberOfGenerationsType	m_NumberOfGenerationsWithMinimalImprovement
NumberOfParticlesType	m_NumberOfParticles
ParameterBoundsType	m_ParameterBounds
ParametersType	m_ParametersBestValue
ParametersType	m_ParametersConvergenceTolerance
std::vector< ParticleData >	m_Particles
double	m_PercentageParticlesConverged
bool	m_PrintSwarm
RandomVariateGeneratorType::IntegerType	m_Seed
std::ostringstream	m_StopConditionDescription
bool	m_UseSeed

Detailed Description

Abstract implementation of a Particle Swarm Optimization (PSO) algorithm.

The PSO algorithm was originally presented in:
J. Kennedy, R. Eberhart, "Particle Swarm Optimization", Proc. IEEE Int. Neural Networks, 1995.

The algorithm is a stochastic global search optimization approach. Optimization is performed by maintaining a swarm of particles that traverse the parameter space, searching for the optimal function value. Associated with each particle are its location and speed, in parameter space.

Swarm initialization is performed within the user supplied parameter bounds using either a uniform distribution or a normal distribution centered on the initial parameter values supplied by the user. The search terminates when the maximal number of iterations has been reached or when the change in the best value in the past $g$ generations is below a threshold and the swarm has collapsed (i.e. best personal particle locations are close to the swarm's best location in parameter space).

The actual optimization procedure, updating the swarm, is performed in the subclasses, required to implement the UpdateSwarm() method.

NOTE: This implementation only performs minimization.

Definition at line 55 of file itkParticleSwarmOptimizerBase.h.

Member Typedef Documentation

typedef SmartPointer<const Self> itk::ParticleSwarmOptimizerBase::ConstPointer

Reimplemented from itk::SingleValuedNonLinearOptimizer.

Reimplemented in itk::InitializationBiasedParticleSwarmOptimizer, and itk::ParticleSwarmOptimizer.

Definition at line 63 of file itkParticleSwarmOptimizerBase.h.

typedef CostFunctionType::MeasureType itk::ParticleSwarmOptimizerBase::MeasureType

Measure type. It defines a type used to return the cost function value.

Reimplemented from itk::SingleValuedNonLinearOptimizer.

Definition at line 84 of file itkParticleSwarmOptimizerBase.h.

typedef unsigned int itk::ParticleSwarmOptimizerBase::NumberOfGenerationsType

Definition at line 83 of file itkParticleSwarmOptimizerBase.h.

typedef unsigned int itk::ParticleSwarmOptimizerBase::NumberOfIterationsType

Definition at line 81 of file itkParticleSwarmOptimizerBase.h.

typedef unsigned int itk::ParticleSwarmOptimizerBase::NumberOfParticlesType

Definition at line 82 of file itkParticleSwarmOptimizerBase.h.

typedef std::vector< std::pair<ParametersType::ValueType, ParametersType::ValueType> > itk::ParticleSwarmOptimizerBase::ParameterBoundsType

Definition at line 69 of file itkParticleSwarmOptimizerBase.h.

typedef SmartPointer<Self> itk::ParticleSwarmOptimizerBase::Pointer

Reimplemented from itk::SingleValuedNonLinearOptimizer.

Reimplemented in itk::InitializationBiasedParticleSwarmOptimizer, and itk::ParticleSwarmOptimizer.

Definition at line 62 of file itkParticleSwarmOptimizerBase.h.

typedef Statistics::MersenneTwisterRandomVariateGenerator itk::ParticleSwarmOptimizerBase::RandomVariateGeneratorType

Definition at line 87 of file itkParticleSwarmOptimizerBase.h.

typedef ParticleSwarmOptimizerBase itk::ParticleSwarmOptimizerBase::Self

Standard "Self" typedef.

Reimplemented from itk::SingleValuedNonLinearOptimizer.

Reimplemented in itk::InitializationBiasedParticleSwarmOptimizer, and itk::ParticleSwarmOptimizer.

Definition at line 60 of file itkParticleSwarmOptimizerBase.h.

typedef SingleValuedNonLinearOptimizer itk::ParticleSwarmOptimizerBase::Superclass

Reimplemented from itk::SingleValuedNonLinearOptimizer.

Reimplemented in itk::InitializationBiasedParticleSwarmOptimizer, and itk::ParticleSwarmOptimizer.

Definition at line 61 of file itkParticleSwarmOptimizerBase.h.

typedef std::vector<ParticleData> itk::ParticleSwarmOptimizerBase::SwarmType

Definition at line 80 of file itkParticleSwarmOptimizerBase.h.

typedef ParametersType::ValueType itk::ParticleSwarmOptimizerBase::ValueType

Definition at line 85 of file itkParticleSwarmOptimizerBase.h.

Constructor & Destructor Documentation

itk::ParticleSwarmOptimizerBase::ParticleSwarmOptimizerBase ( ) [protected]

virtual itk::ParticleSwarmOptimizerBase::~ParticleSwarmOptimizerBase ( ) [protected, virtual]

itk::ParticleSwarmOptimizerBase::ParticleSwarmOptimizerBase ( const Self & ) [protected]

Member Function Documentation

void itk::ParticleSwarmOptimizerBase::ClearSwarm ( )

Specify the initial swarm. Useful for evaluating PSO variants. If the initial swarm is set it will be used. To revert to random initialization (uniform or normal particle distributions) set using an empty swarm.

void itk::ParticleSwarmOptimizerBase::FileInitialization ( ) [protected]

virtual MeasureType itk::ParticleSwarmOptimizerBase::GetFunctionConvergenceTolerance ( ) [virtual]

virtual bool itk::ParticleSwarmOptimizerBase::GetInitializeNormalDistribution ( ) [virtual]

virtual NumberOfIterationsType itk::ParticleSwarmOptimizerBase::GetMaximalNumberOfIterations ( ) [virtual]

virtual const char* itk::ParticleSwarmOptimizerBase::GetNameOfClass ( ) const [virtual]

Run-time type information (and related methods).

Reimplemented from itk::SingleValuedNonLinearOptimizer.

Reimplemented in itk::InitializationBiasedParticleSwarmOptimizer, and itk::ParticleSwarmOptimizer.

virtual NumberOfGenerationsType itk::ParticleSwarmOptimizerBase::GetNumberOfGenerationsWithMinimalImprovement ( ) [virtual]

virtual NumberOfParticlesType itk::ParticleSwarmOptimizerBase::GetNumberOfParticles ( ) [virtual]

ParameterBoundsType itk::ParticleSwarmOptimizerBase::GetParameterBounds ( ) const

virtual ParametersType itk::ParticleSwarmOptimizerBase::GetParametersConvergenceTolerance ( ) [virtual]

virtual double itk::ParticleSwarmOptimizerBase::GetPercentageParticlesConverged ( ) [virtual]

virtual bool itk::ParticleSwarmOptimizerBase::GetPrintSwarm ( ) [virtual]

virtual RandomVariateGeneratorType::IntegerType itk::ParticleSwarmOptimizerBase::GetSeed ( ) [virtual]

virtual const std::string itk::ParticleSwarmOptimizerBase::GetStopConditionDescription ( ) const [virtual]

Get the reason for termination

Reimplemented from itk::Optimizer.

virtual bool itk::ParticleSwarmOptimizerBase::GetUseSeed ( ) [virtual]

MeasureType itk::ParticleSwarmOptimizerBase::GetValue ( ) const

Get the function value for the current position. NOTE: This value is only valid during and after the execution of the StartOptimization() method.

virtual void itk::ParticleSwarmOptimizerBase::Initialize ( ) [protected, virtual]

Initialize the particle swarm, and seed the random number generator.

virtual void itk::ParticleSwarmOptimizerBase::InitializeNormalDistributionOff ( ) [virtual]

virtual void itk::ParticleSwarmOptimizerBase::InitializeNormalDistributionOn ( ) [virtual]

void itk::ParticleSwarmOptimizerBase::operator= ( const Self & ) [protected]

Types inherited from the superclass

Reimplemented from itk::SingleValuedNonLinearOptimizer.

Reimplemented in itk::InitializationBiasedParticleSwarmOptimizer, and itk::ParticleSwarmOptimizer.

void itk::ParticleSwarmOptimizerBase::PrintParamtersType	(	const ParametersType &	x,
		std::ostream &	os
	)		const `[protected]`

void itk::ParticleSwarmOptimizerBase::PrintSelf	(	std::ostream &	os,
		Indent	indent
	)		const `[protected, virtual]`

Methods invoked by Print() to print information about the object including superclasses. Typically not called by the user (use Print() instead) but used in the hierarchical print process to combine the output of several classes.

Reimplemented from itk::SingleValuedNonLinearOptimizer.

Reimplemented in itk::InitializationBiasedParticleSwarmOptimizer, and itk::ParticleSwarmOptimizer.

void itk::ParticleSwarmOptimizerBase::PrintSwarm	(	std::ostream &	os,
		Indent	indent
	)		const

Print the swarm information to the given output stream. Each line (particle data) is of the form: current_parameters current_velocity current_value best_parameters best_value

virtual void itk::ParticleSwarmOptimizerBase::PrintSwarmOff ( ) [virtual]

virtual void itk::ParticleSwarmOptimizerBase::PrintSwarmOn ( ) [virtual]

void itk::ParticleSwarmOptimizerBase::RandomInitialization ( ) [protected]

virtual void itk::ParticleSwarmOptimizerBase::SetFunctionConvergenceTolerance ( MeasureType _arg ) [virtual]

The optimization algorithm will terminate when the function improvement in the last m_NumberOfGenerationsWithMinimalImprovement generations is less than m_FunctionConvergenceTolerance and the maximal distance between particles and the best particle in each dimension is less than m_ParametersConvergenceTolerance[i] for the specified percentage of the particles. That is, we haven't improved the best function value for a while and in the parameter space most (m%) of our particles attained their best value close to the swarm's best value. NOTE: The use of different tolerances for each dimension is desired when optimizing over non-commensurate parameters (e.g. rotation and translation). Alternatively, we could use ITK's parameter scaling approach. The current approach seems more intuitive.

virtual void itk::ParticleSwarmOptimizerBase::SetInitializeNormalDistribution ( bool _arg ) [virtual]

Specify whether to initialize the particles using a normal distribution centered on the user supplied initial value or a uniform distribution. If the optimum is expected to be near the initial value it is likely that initializing with a normal distribution will result in faster convergence.

void itk::ParticleSwarmOptimizerBase::SetInitialSwarm ( const SwarmType & initialSwarm )

Specify the initial swarm. Useful for evaluating PSO variants. If the initial swarm is set it will be used. To revert to random initialization (uniform or normal particle distributions) set using an empty swarm.

virtual void itk::ParticleSwarmOptimizerBase::SetMaximalNumberOfIterations ( NumberOfIterationsType _arg ) [virtual]

Set/Get maximal number of iterations - the maximal number of function evaluations is m_MaximalNumberOfIterations*m_NumberOfParticles

virtual void itk::ParticleSwarmOptimizerBase::SetNumberOfGenerationsWithMinimalImprovement ( NumberOfGenerationsType _arg ) [virtual]

Set/Get the number of generations to continue with minimal improvement in the function value, |f_best(g_i) - f_best(g_k)|<threshold where k <= i+NumberOfGenerationsWithMinimalImprovement Minimal value is one.

void itk::ParticleSwarmOptimizerBase::SetNumberOfParticles ( NumberOfParticlesType n )

Set/Get number of particles in the swarm - the maximal number of function evaluations is m_MaximalNumberOfIterations*m_NumberOfParticles

virtual void itk::ParticleSwarmOptimizerBase::SetParameterBounds ( ParameterBoundsType & bounds ) [virtual]

Set/Get the parameter bounds. Search for optimal value is inside these bounds. NOTE: It is assumed that the first entry is the minimal value, second is the maximal value.

void itk::ParticleSwarmOptimizerBase::SetParameterBounds	(	std::pair< ParametersType::ValueType, ParametersType::ValueType > &	bounds,
		unsigned int	n
	)

Set/Get the parameter bounds. Search for optimal value is inside these bounds. NOTE: It is assumed that the first entry is the minimal value, second is the maximal value.

void itk::ParticleSwarmOptimizerBase::SetParametersConvergenceTolerance	(	ValueType	convergenceTolerance,
		unsigned int	sz
	)

Set parameters convergence tolerance using the same value for all, sz, parameters

virtual void itk::ParticleSwarmOptimizerBase::SetParametersConvergenceTolerance ( ParametersType _arg ) [virtual]

virtual void itk::ParticleSwarmOptimizerBase::SetPercentageParticlesConverged ( double _arg ) [virtual]

virtual void itk::ParticleSwarmOptimizerBase::SetPrintSwarm ( bool _arg ) [virtual]

Indicate whether or not to output the swarm information when printing an object. By default this option is turned off as it generates too much information.

virtual void itk::ParticleSwarmOptimizerBase::SetSeed ( RandomVariateGeneratorType::IntegerType _arg ) [virtual]

Set the random number seed for the swarm. Use this method to produce reaptible results, typically, for testing.

virtual void itk::ParticleSwarmOptimizerBase::SetUseSeed ( bool _arg ) [virtual]

Use a specific seed to initialize the random number generator. If On, use m_Seed to seed the random number generator. Default is Off.

void itk::ParticleSwarmOptimizerBase::StartOptimization ( void ) [virtual]

Start optimization.

Reimplemented from itk::Optimizer.

virtual void itk::ParticleSwarmOptimizerBase::UpdateSwarm ( ) [protected, pure virtual]

Implement your update rule in this function.

Implemented in itk::InitializationBiasedParticleSwarmOptimizer, and itk::ParticleSwarmOptimizer.

virtual void itk::ParticleSwarmOptimizerBase::UseSeedOff ( ) [virtual]