#include <itkInitializationBiasedParticleSwarmOptimizer.h>

Inheritance diagram for itk::InitializationBiasedParticleSwarmOptimizer:

Collaboration diagram for itk::InitializationBiasedParticleSwarmOptimizer:

Public Types
using	CoefficientType = double

using	ConstPointer = SmartPointer< const Self >

using	Pointer = SmartPointer< Self >

using	Self = InitializationBiasedParticleSwarmOptimizer

using	Superclass = ParticleSwarmOptimizerBase

Public Types inherited from itk::ParticleSwarmOptimizerBase
using	ConstPointer = SmartPointer< const Self >

using	MeasureType = CostFunctionType::MeasureType

using	NumberOfGenerationsType = unsigned int

using	NumberOfIterationsType = unsigned int

using	NumberOfParticlesType = unsigned int

using	ParameterBoundsType = std::vector< std::pair< ParametersType::ValueType, ParametersType::ValueType > >

using	Pointer = SmartPointer< Self >

using	RandomVariateGeneratorType = Statistics::MersenneTwisterRandomVariateGenerator

using	Self = ParticleSwarmOptimizerBase

using	Superclass = SingleValuedNonLinearOptimizer

using	SwarmType = std::vector< ParticleData >

using	ValueType = ParametersType::ValueType

Public Types inherited from itk::SingleValuedNonLinearOptimizer
using	ConstPointer = SmartPointer< const Self >

using	CostFunctionPointer = CostFunctionType::Pointer

using	CostFunctionType = SingleValuedCostFunction

using	DerivativeType = CostFunctionType::DerivativeType

using	MeasureType = CostFunctionType::MeasureType

using	ParametersType = Superclass::ParametersType

using	Pointer = SmartPointer< Self >

using	Self = SingleValuedNonLinearOptimizer

using	Superclass = NonLinearOptimizer

Public Types inherited from itk::NonLinearOptimizer
using	ConstPointer = SmartPointer< const Self >

using	ParametersType = Superclass::ParametersType

using	Pointer = SmartPointer< Self >

using	ScalesType = Superclass::ScalesType

using	Self = NonLinearOptimizer

using	Superclass = Optimizer

Public Types inherited from itk::Optimizer
using	ConstPointer = SmartPointer< const Self >

using	ParametersType = OptimizerParameters< double >

using	Pointer = SmartPointer< Self >

using	ScalesType = Array< double >

using	Self = Optimizer

using	Superclass = Object

Public Types inherited from itk::Object
using	ConstPointer = SmartPointer< const Self >

using	Pointer = SmartPointer< Self >

using	Self = Object

using	Superclass = LightObject

Public Types inherited from itk::LightObject
using	ConstPointer = SmartPointer< const Self >

using	Pointer = SmartPointer< Self >

using	Self = LightObject

Public Member Functions
virtual ::itk::LightObject::Pointer	CreateAnother () const

virtual const char *	GetNameOfClass () const

Public Member Functions inherited from itk::ParticleSwarmOptimizerBase
virtual void	SetInitializeNormalDistribution (bool _arg)

virtual bool	GetInitializeNormalDistribution ()

virtual void	InitializeNormalDistributionOn ()

virtual void	InitializeNormalDistributionOff ()

void	SetInitialSwarm (const SwarmType &initialSwarm)

void	ClearSwarm ()

virtual void	SetPrintSwarm (bool _arg)

virtual bool	GetPrintSwarm ()

virtual void	PrintSwarmOn ()

virtual void	PrintSwarmOff ()

void	StartOptimization () override

void	SetNumberOfParticles (NumberOfParticlesType n)

virtual NumberOfParticlesType	GetNumberOfParticles ()

virtual void	SetMaximalNumberOfIterations (NumberOfIterationsType _arg)

virtual NumberOfIterationsType	GetMaximalNumberOfIterations ()

virtual void	SetNumberOfGenerationsWithMinimalImprovement (NumberOfGenerationsType _arg)

virtual NumberOfGenerationsType	GetNumberOfGenerationsWithMinimalImprovement ()

virtual void	SetParameterBounds (ParameterBoundsType &bounds)

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

ParameterBoundsType	GetParameterBounds () const

virtual void	SetFunctionConvergenceTolerance (MeasureType _arg)

virtual MeasureType	GetFunctionConvergenceTolerance ()

void	SetParametersConvergenceTolerance (ValueType convergenceTolerance, unsigned int sz)

virtual void	SetParametersConvergenceTolerance (ParametersType _arg)

virtual ParametersType	GetParametersConvergenceTolerance ()

virtual double	GetPercentageParticlesConverged ()

virtual void	SetPercentageParticlesConverged (double _arg)

virtual void	SetSeed (RandomVariateGeneratorType::IntegerType _arg)

virtual RandomVariateGeneratorType::IntegerType	GetSeed ()

virtual void	SetUseSeed (bool _arg)

virtual bool	GetUseSeed ()

virtual void	UseSeedOn ()

virtual void	UseSeedOff ()

MeasureType	GetValue () const

const std::string	GetStopConditionDescription () const override

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

Public Member Functions inherited from itk::SingleValuedNonLinearOptimizer
virtual ::itk::LightObject::Pointer	CreateAnother () const

virtual const CostFunctionType *	GetCostFunction () const

virtual CostFunctionType *	GetModifiableCostFunction ()

MeasureType	GetValue (const ParametersType &parameters) const

virtual void	SetCostFunction (CostFunctionType *costFunction)

Public Member Functions inherited from itk::Optimizer
virtual const ParametersType &	GetInitialPosition () const

virtual void	SetInitialPosition (const ParametersType &param)

void	SetScales (const ScalesType &scales)

virtual const ScalesType &	GetScales () const

virtual const ScalesType &	GetInverseScales () const

virtual const ParametersType &	GetCurrentPosition () const

Public Member Functions inherited from itk::Object
unsigned long	AddObserver (const EventObject &event, Command *)

unsigned long	AddObserver (const EventObject &event, Command *) const

unsigned long	AddObserver (const EventObject &event, std::function< void(const EventObject &)> function) const

virtual void	DebugOff () const

virtual void	DebugOn () const

Command *	GetCommand (unsigned long tag)

bool	GetDebug () const

MetaDataDictionary &	GetMetaDataDictionary ()

const MetaDataDictionary &	GetMetaDataDictionary () const

virtual ModifiedTimeType	GetMTime () const

virtual const TimeStamp &	GetTimeStamp () const

bool	HasObserver (const EventObject &event) const

void	InvokeEvent (const EventObject &)

void	InvokeEvent (const EventObject &) const

virtual void	Modified () const

void	Register () const override

void	RemoveAllObservers ()

void	RemoveObserver (unsigned long tag)

void	SetDebug (bool debugFlag) const

void	SetReferenceCount (int) override

void	UnRegister () const noexcept override

void	SetMetaDataDictionary (const MetaDataDictionary &rhs)

void	SetMetaDataDictionary (MetaDataDictionary &&rrhs)

virtual void	SetObjectName (std::string _arg)

virtual const std::string &	GetObjectName () const

Public Member Functions inherited from itk::LightObject
Pointer	Clone () const

virtual void	Delete ()

virtual int	GetReferenceCount () const

void	Print (std::ostream &os, Indent indent=0) const

Static Public Member Functions
static Pointer	New ()

Static Public Member Functions inherited from itk::SingleValuedNonLinearOptimizer
static Pointer	New ()

Static Public Member Functions inherited from itk::NonLinearOptimizer
static Pointer	New ()

Static Public Member Functions inherited from itk::Optimizer
static Pointer	New ()

Static Public Member Functions inherited from itk::Object
static bool	GetGlobalWarningDisplay ()

static void	GlobalWarningDisplayOff ()

static void	GlobalWarningDisplayOn ()

static Pointer	New ()

static void	SetGlobalWarningDisplay (bool val)

Static Public Member Functions inherited from itk::LightObject
static void	BreakOnError ()

static Pointer	New ()

ParametersType::ValueType	m_InertiaCoefficient

ParametersType::ValueType	m_PersonalCoefficient

ParametersType::ValueType	m_GlobalCoefficient

ParametersType::ValueType	m_InitializationCoefficient

virtual void	SetInertiaCoefficient (CoefficientType _arg)

virtual CoefficientType	GetInertiaCoefficient ()

virtual void	SetPersonalCoefficient (CoefficientType _arg)

virtual CoefficientType	GetPersonalCoefficient ()

virtual void	SetGlobalCoefficient (CoefficientType _arg)

virtual CoefficientType	GetGlobalCoefficient ()

virtual void	SetInitializationCoefficient (CoefficientType _arg)

virtual CoefficientType	GetInitializationCoefficient ()

	InitializationBiasedParticleSwarmOptimizer ()

	~InitializationBiasedParticleSwarmOptimizer () override=default

void	PrintSelf (std::ostream &os, Indent indent) const override

void	UpdateSwarm () override

Additional Inherited Members
Protected Member Functions inherited from itk::ParticleSwarmOptimizerBase
	ParticleSwarmOptimizerBase ()

	~ParticleSwarmOptimizerBase () override

void	PrintSelf (std::ostream &os, Indent indent) const override

void	PrintParamtersType (const ParametersType &x, std::ostream &os) const

virtual void	ValidateSettings ()

virtual void	Initialize ()

void	RandomInitialization ()

void	FileInitialization ()

Protected Member Functions inherited from itk::SingleValuedNonLinearOptimizer
void	PrintSelf (std::ostream &os, Indent indent) const override

	SingleValuedNonLinearOptimizer ()

	~SingleValuedNonLinearOptimizer () override=default

Protected Member Functions inherited from itk::NonLinearOptimizer
	NonLinearOptimizer ()=default

	~NonLinearOptimizer () override

Protected Member Functions inherited from itk::Optimizer
	Optimizer ()

	~Optimizer () override=default

virtual void	SetCurrentPosition (const ParametersType &param)

Protected Member Functions inherited from itk::Object
	Object ()

	~Object () override

bool	PrintObservers (std::ostream &os, Indent indent) const

virtual void	SetTimeStamp (const TimeStamp &timeStamp)

Protected Member Functions inherited from itk::LightObject
virtual LightObject::Pointer	InternalClone () const

	LightObject ()

virtual void	PrintHeader (std::ostream &os, Indent indent) const

virtual void	PrintTrailer (std::ostream &os, Indent indent) const

virtual	~LightObject ()

Protected Attributes inherited from itk::ParticleSwarmOptimizerBase
bool	m_PrintSwarm

std::ostringstream	m_StopConditionDescription

bool	m_InitializeNormalDistribution

NumberOfParticlesType	m_NumberOfParticles

NumberOfIterationsType	m_MaximalNumberOfIterations

NumberOfGenerationsType	m_NumberOfGenerationsWithMinimalImprovement

ParameterBoundsType	m_ParameterBounds

ParametersType	m_ParametersConvergenceTolerance

double	m_PercentageParticlesConverged

CostFunctionType::MeasureType	m_FunctionConvergenceTolerance

std::vector< ParticleData >	m_Particles

CostFunctionType::MeasureType	m_FunctionBestValue { 0 }

std::vector< MeasureType >	m_FunctionBestValueMemory

ParametersType	m_ParametersBestValue

NumberOfIterationsType	m_IterationIndex { 0 }

RandomVariateGeneratorType::IntegerType	m_Seed

bool	m_UseSeed

Protected Attributes inherited from itk::SingleValuedNonLinearOptimizer
CostFunctionPointer	m_CostFunction

Protected Attributes inherited from itk::Optimizer
bool	m_ScalesInitialized { false }

ParametersType	m_CurrentPosition

Protected Attributes inherited from itk::LightObject
std::atomic< int >	m_ReferenceCount

Detailed Description

Implementation of a biased/regularized Particle Swarm Optimization (PSO) algorithm.

This PSO algorithm was originally described in: M. P. Wachowiak, R. Smolikova, Y. Zheng, J. M. Zurada, A. S. Elmaghraby, "An approach to multimodal biomedical image registration utilizing particle swarm optimization", IEEE Trans. Evol. Comput., vol. 8(3): 289-301, 2004.

The algorithm uses a stochastic optimization approach. Optimization is performed by maintaining a swarm (flock) 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. A particle's next location is determined by its current location, its current speed, the location of the best function value it previously encountered, the location of the best function value the particles in its neighborhood previously encountered and the initial position the user specified.

The assumption is that the user's initial parameter settings are close to the minimum, which is often the case for registration. The initial parameter values are incorporated into the PSO's update rules, biasing the search in their direction. The swarms update equations are thus:

$v_i(t+1) = wv_i(t) + c_1u_1(p_i-x_i(t)) + c_2u_2(p_g-x_i(t)) + c_3u_3(x_{init} - x_i(t))$ $x_i(t+1) = clampToBounds(x_i(t) + v_i(t+1))$

where $u_i$ are $~U(0,1)$ and $w,c_1,c_2, c_3$ are user selected weights, and c_3 is linearly decreased per iteration so that it is in $c_3=initial, 0$ .

Swarm initialization is performed within the user supplied parameter bounds using a uniform distribution or a normal distribution centered on the initial parameter values supplied by the user, $x_{init}$ . 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. particles are close to each other in parameter space).

Note: This implementation only performs minimization.

Definition at line 72 of file itkInitializationBiasedParticleSwarmOptimizer.h.

Member Typedef Documentation

◆ CoefficientType

using itk::InitializationBiasedParticleSwarmOptimizer::CoefficientType = double

Definition at line 83 of file itkInitializationBiasedParticleSwarmOptimizer.h.

◆ ConstPointer

using itk::InitializationBiasedParticleSwarmOptimizer::ConstPointer = SmartPointer<const Self>

Definition at line 81 of file itkInitializationBiasedParticleSwarmOptimizer.h.

◆ Pointer

using itk::InitializationBiasedParticleSwarmOptimizer::Pointer = SmartPointer<Self>

Definition at line 80 of file itkInitializationBiasedParticleSwarmOptimizer.h.

◆ Self

using itk::InitializationBiasedParticleSwarmOptimizer::Self = InitializationBiasedParticleSwarmOptimizer

Standard "Self" type alias.

Definition at line 78 of file itkInitializationBiasedParticleSwarmOptimizer.h.

◆ Superclass

using itk::InitializationBiasedParticleSwarmOptimizer::Superclass = ParticleSwarmOptimizerBase

Definition at line 79 of file itkInitializationBiasedParticleSwarmOptimizer.h.

Constructor & Destructor Documentation

◆ InitializationBiasedParticleSwarmOptimizer()

itk::InitializationBiasedParticleSwarmOptimizer::InitializationBiasedParticleSwarmOptimizer ( )

protected

The Particle swarm optimizer uses the following update formula:

$c_3 = c_{3initial}(1.0 - IterationIndex/MaximalNumberOfIterations)$

$v_i(t+1) = w*v_i(t) + c_1*uniform(0,1)*(p_i-x_i(t)) + c_2*uniform(0,1)*(p_g-x_i(t)) + c_3*uniform(0,1)*(x_{init}-x_i(t))$

$x_i(t+1) = clampToBounds(x_i(t) + v_i(t+1))$

where $w$ - inertia constant $c_1$ - personal coefficient $c_2$ - global coefficient $c_3$ - initial location coefficient $p_i$ - parameters yielding the best function value obtained by this particle $p_g$ - parameters yielding the best function value obtained by all particles $x_{init}$ - initial parameter values provided by user

◆ ~InitializationBiasedParticleSwarmOptimizer()

itk::InitializationBiasedParticleSwarmOptimizer::~InitializationBiasedParticleSwarmOptimizer ( )

overrideprotecteddefault

The Particle swarm optimizer uses the following update formula:

$c_3 = c_{3initial}(1.0 - IterationIndex/MaximalNumberOfIterations)$

$v_i(t+1) = w*v_i(t) + c_1*uniform(0,1)*(p_i-x_i(t)) + c_2*uniform(0,1)*(p_g-x_i(t)) + c_3*uniform(0,1)*(x_{init}-x_i(t))$

$x_i(t+1) = clampToBounds(x_i(t) + v_i(t+1))$

where $w$ - inertia constant $c_1$ - personal coefficient $c_2$ - global coefficient $c_3$ - initial location coefficient $p_i$ - parameters yielding the best function value obtained by this particle $p_g$ - parameters yielding the best function value obtained by all particles $x_{init}$ - initial parameter values provided by user

Member Function Documentation

◆ CreateAnother()

virtual::itk::LightObject::Pointer itk::InitializationBiasedParticleSwarmOptimizer::CreateAnother ( ) const

virtual

Create an object from an instance, potentially deferring to a factory. This method allows you to create an instance of an object that is exactly the same type as the referring object. This is useful in cases where an object has been cast back to a base class.

Reimplemented from itk::Object.

◆ GetGlobalCoefficient()

virtual CoefficientType itk::InitializationBiasedParticleSwarmOptimizer::GetGlobalCoefficient ( )

virtual

The Particle swarm optimizer uses the following update formula:

$c_3 = c_{3initial}(1.0 - IterationIndex/MaximalNumberOfIterations)$

$v_i(t+1) = w*v_i(t) + c_1*uniform(0,1)*(p_i-x_i(t)) + c_2*uniform(0,1)*(p_g-x_i(t)) + c_3*uniform(0,1)*(x_{init}-x_i(t))$

$x_i(t+1) = clampToBounds(x_i(t) + v_i(t+1))$

where $w$ - inertia constant $c_1$ - personal coefficient $c_2$ - global coefficient $c_3$ - initial location coefficient $p_i$ - parameters yielding the best function value obtained by this particle $p_g$ - parameters yielding the best function value obtained by all particles $x_{init}$ - initial parameter values provided by user

◆ GetInertiaCoefficient()

virtual CoefficientType itk::InitializationBiasedParticleSwarmOptimizer::GetInertiaCoefficient ( )

virtual

The Particle swarm optimizer uses the following update formula:

$c_3 = c_{3initial}(1.0 - IterationIndex/MaximalNumberOfIterations)$

$v_i(t+1) = w*v_i(t) + c_1*uniform(0,1)*(p_i-x_i(t)) + c_2*uniform(0,1)*(p_g-x_i(t)) + c_3*uniform(0,1)*(x_{init}-x_i(t))$

$x_i(t+1) = clampToBounds(x_i(t) + v_i(t+1))$

where $w$ - inertia constant $c_1$ - personal coefficient $c_2$ - global coefficient $c_3$ - initial location coefficient $p_i$ - parameters yielding the best function value obtained by this particle $p_g$ - parameters yielding the best function value obtained by all particles $x_{init}$ - initial parameter values provided by user

◆ GetInitializationCoefficient()

virtual CoefficientType itk::InitializationBiasedParticleSwarmOptimizer::GetInitializationCoefficient ( )

virtual

The Particle swarm optimizer uses the following update formula:

$c_3 = c_{3initial}(1.0 - IterationIndex/MaximalNumberOfIterations)$

$v_i(t+1) = w*v_i(t) + c_1*uniform(0,1)*(p_i-x_i(t)) + c_2*uniform(0,1)*(p_g-x_i(t)) + c_3*uniform(0,1)*(x_{init}-x_i(t))$

$x_i(t+1) = clampToBounds(x_i(t) + v_i(t+1))$

where $w$ - inertia constant $c_1$ - personal coefficient $c_2$ - global coefficient $c_3$ - initial location coefficient $p_i$ - parameters yielding the best function value obtained by this particle $p_g$ - parameters yielding the best function value obtained by all particles $x_{init}$ - initial parameter values provided by user

◆ GetNameOfClass()

virtual const char* itk::InitializationBiasedParticleSwarmOptimizer::GetNameOfClass ( ) const

virtual

Run-time type information (and related methods).

Reimplemented from itk::ParticleSwarmOptimizerBase.

◆ GetPersonalCoefficient()

virtual CoefficientType itk::InitializationBiasedParticleSwarmOptimizer::GetPersonalCoefficient ( )

virtual

The Particle swarm optimizer uses the following update formula:

$c_3 = c_{3initial}(1.0 - IterationIndex/MaximalNumberOfIterations)$

$v_i(t+1) = w*v_i(t) + c_1*uniform(0,1)*(p_i-x_i(t)) + c_2*uniform(0,1)*(p_g-x_i(t)) + c_3*uniform(0,1)*(x_{init}-x_i(t))$

$x_i(t+1) = clampToBounds(x_i(t) + v_i(t+1))$

where $w$ - inertia constant $c_1$ - personal coefficient $c_2$ - global coefficient $c_3$ - initial location coefficient $p_i$ - parameters yielding the best function value obtained by this particle $p_g$ - parameters yielding the best function value obtained by all particles $x_{init}$ - initial parameter values provided by user

◆ New()

static Pointer itk::InitializationBiasedParticleSwarmOptimizer::New ( )

static

Method for creation through the object factory.

◆ PrintSelf()

void itk::InitializationBiasedParticleSwarmOptimizer::PrintSelf	(	std::ostream &	os,
		Indent	indent
	)		const

overrideprotectedvirtual

The Particle swarm optimizer uses the following update formula:

$c_3 = c_{3initial}(1.0 - IterationIndex/MaximalNumberOfIterations)$

$v_i(t+1) = w*v_i(t) + c_1*uniform(0,1)*(p_i-x_i(t)) + c_2*uniform(0,1)*(p_g-x_i(t)) + c_3*uniform(0,1)*(x_{init}-x_i(t))$

$x_i(t+1) = clampToBounds(x_i(t) + v_i(t+1))$

where $w$ - inertia constant $c_1$ - personal coefficient $c_2$ - global coefficient $c_3$ - initial location coefficient $p_i$ - parameters yielding the best function value obtained by this particle $p_g$ - parameters yielding the best function value obtained by all particles $x_{init}$ - initial parameter values provided by user

Reimplemented from itk::Object.

◆ SetGlobalCoefficient()

virtual void itk::InitializationBiasedParticleSwarmOptimizer::SetGlobalCoefficient ( CoefficientType _arg )

virtual

The Particle swarm optimizer uses the following update formula:

$c_3 = c_{3initial}(1.0 - IterationIndex/MaximalNumberOfIterations)$

$v_i(t+1) = w*v_i(t) + c_1*uniform(0,1)*(p_i-x_i(t)) + c_2*uniform(0,1)*(p_g-x_i(t)) + c_3*uniform(0,1)*(x_{init}-x_i(t))$

$x_i(t+1) = clampToBounds(x_i(t) + v_i(t+1))$

where $w$ - inertia constant $c_1$ - personal coefficient $c_2$ - global coefficient $c_3$ - initial location coefficient $p_i$ - parameters yielding the best function value obtained by this particle $p_g$ - parameters yielding the best function value obtained by all particles $x_{init}$ - initial parameter values provided by user

◆ SetInertiaCoefficient()

virtual void itk::InitializationBiasedParticleSwarmOptimizer::SetInertiaCoefficient ( CoefficientType _arg )

virtual

The Particle swarm optimizer uses the following update formula:

$c_3 = c_{3initial}(1.0 - IterationIndex/MaximalNumberOfIterations)$

$v_i(t+1) = w*v_i(t) + c_1*uniform(0,1)*(p_i-x_i(t)) + c_2*uniform(0,1)*(p_g-x_i(t)) + c_3*uniform(0,1)*(x_{init}-x_i(t))$

$x_i(t+1) = clampToBounds(x_i(t) + v_i(t+1))$

where $w$ - inertia constant $c_1$ - personal coefficient $c_2$ - global coefficient $c_3$ - initial location coefficient $p_i$ - parameters yielding the best function value obtained by this particle $p_g$ - parameters yielding the best function value obtained by all particles $x_{init}$ - initial parameter values provided by user

◆ SetInitializationCoefficient()

virtual void itk::InitializationBiasedParticleSwarmOptimizer::SetInitializationCoefficient ( CoefficientType _arg )

virtual

The Particle swarm optimizer uses the following update formula:

$c_3 = c_{3initial}(1.0 - IterationIndex/MaximalNumberOfIterations)$

$v_i(t+1) = w*v_i(t) + c_1*uniform(0,1)*(p_i-x_i(t)) + c_2*uniform(0,1)*(p_g-x_i(t)) + c_3*uniform(0,1)*(x_{init}-x_i(t))$

$x_i(t+1) = clampToBounds(x_i(t) + v_i(t+1))$

where $w$ - inertia constant $c_1$ - personal coefficient $c_2$ - global coefficient $c_3$ - initial location coefficient $p_i$ - parameters yielding the best function value obtained by this particle $p_g$ - parameters yielding the best function value obtained by all particles $x_{init}$ - initial parameter values provided by user

◆ SetPersonalCoefficient()

virtual void itk::InitializationBiasedParticleSwarmOptimizer::SetPersonalCoefficient ( CoefficientType _arg )

virtual

The Particle swarm optimizer uses the following update formula:

$c_3 = c_{3initial}(1.0 - IterationIndex/MaximalNumberOfIterations)$

$v_i(t+1) = w*v_i(t) + c_1*uniform(0,1)*(p_i-x_i(t)) + c_2*uniform(0,1)*(p_g-x_i(t)) + c_3*uniform(0,1)*(x_{init}-x_i(t))$

$x_i(t+1) = clampToBounds(x_i(t) + v_i(t+1))$

where $w$ - inertia constant $c_1$ - personal coefficient $c_2$ - global coefficient $c_3$ - initial location coefficient $p_i$ - parameters yielding the best function value obtained by this particle $p_g$ - parameters yielding the best function value obtained by all particles $x_{init}$ - initial parameter values provided by user

◆ UpdateSwarm()

void itk::InitializationBiasedParticleSwarmOptimizer::UpdateSwarm ( )

overrideprotectedvirtual

The Particle swarm optimizer uses the following update formula:

$c_3 = c_{3initial}(1.0 - IterationIndex/MaximalNumberOfIterations)$

$v_i(t+1) = w*v_i(t) + c_1*uniform(0,1)*(p_i-x_i(t)) + c_2*uniform(0,1)*(p_g-x_i(t)) + c_3*uniform(0,1)*(x_{init}-x_i(t))$

$x_i(t+1) = clampToBounds(x_i(t) + v_i(t+1))$

where $w$ - inertia constant $c_1$ - personal coefficient $c_2$ - global coefficient $c_3$ - initial location coefficient $p_i$ - parameters yielding the best function value obtained by this particle $p_g$ - parameters yielding the best function value obtained by all particles $x_{init}$ - initial parameter values provided by user

Implements itk::ParticleSwarmOptimizerBase.

Member Data Documentation

◆ m_GlobalCoefficient

ParametersType::ValueType itk::InitializationBiasedParticleSwarmOptimizer::m_GlobalCoefficient

private

The Particle swarm optimizer uses the following update formula:

$c_3 = c_{3initial}(1.0 - IterationIndex/MaximalNumberOfIterations)$

$v_i(t+1) = w*v_i(t) + c_1*uniform(0,1)*(p_i-x_i(t)) + c_2*uniform(0,1)*(p_g-x_i(t)) + c_3*uniform(0,1)*(x_{init}-x_i(t))$

$x_i(t+1) = clampToBounds(x_i(t) + v_i(t+1))$

where $w$ - inertia constant $c_1$ - personal coefficient $c_2$ - global coefficient $c_3$ - initial location coefficient $p_i$ - parameters yielding the best function value obtained by this particle $p_g$ - parameters yielding the best function value obtained by all particles $x_{init}$ - initial parameter values provided by user

Definition at line 128 of file itkInitializationBiasedParticleSwarmOptimizer.h.

◆ m_InertiaCoefficient

ParametersType::ValueType itk::InitializationBiasedParticleSwarmOptimizer::m_InertiaCoefficient

private

The Particle swarm optimizer uses the following update formula:

$c_3 = c_{3initial}(1.0 - IterationIndex/MaximalNumberOfIterations)$

$v_i(t+1) = w*v_i(t) + c_1*uniform(0,1)*(p_i-x_i(t)) + c_2*uniform(0,1)*(p_g-x_i(t)) + c_3*uniform(0,1)*(x_{init}-x_i(t))$

$x_i(t+1) = clampToBounds(x_i(t) + v_i(t+1))$

where $w$ - inertia constant $c_1$ - personal coefficient $c_2$ - global coefficient $c_3$ - initial location coefficient $p_i$ - parameters yielding the best function value obtained by this particle $p_g$ - parameters yielding the best function value obtained by all particles $x_{init}$ - initial parameter values provided by user

Definition at line 126 of file itkInitializationBiasedParticleSwarmOptimizer.h.

◆ m_InitializationCoefficient

ParametersType::ValueType itk::InitializationBiasedParticleSwarmOptimizer::m_InitializationCoefficient

private

The Particle swarm optimizer uses the following update formula:

$c_3 = c_{3initial}(1.0 - IterationIndex/MaximalNumberOfIterations)$

$v_i(t+1) = w*v_i(t) + c_1*uniform(0,1)*(p_i-x_i(t)) + c_2*uniform(0,1)*(p_g-x_i(t)) + c_3*uniform(0,1)*(x_{init}-x_i(t))$

$x_i(t+1) = clampToBounds(x_i(t) + v_i(t+1))$

where $w$ - inertia constant $c_1$ - personal coefficient $c_2$ - global coefficient $c_3$ - initial location coefficient $p_i$ - parameters yielding the best function value obtained by this particle $p_g$ - parameters yielding the best function value obtained by all particles $x_{init}$ - initial parameter values provided by user

Definition at line 129 of file itkInitializationBiasedParticleSwarmOptimizer.h.

◆ m_PersonalCoefficient

ParametersType::ValueType itk::InitializationBiasedParticleSwarmOptimizer::m_PersonalCoefficient

private

The Particle swarm optimizer uses the following update formula:

$c_3 = c_{3initial}(1.0 - IterationIndex/MaximalNumberOfIterations)$

$v_i(t+1) = w*v_i(t) + c_1*uniform(0,1)*(p_i-x_i(t)) + c_2*uniform(0,1)*(p_g-x_i(t)) + c_3*uniform(0,1)*(x_{init}-x_i(t))$

$x_i(t+1) = clampToBounds(x_i(t) + v_i(t+1))$

where $w$ - inertia constant $c_1$ - personal coefficient $c_2$ - global coefficient $c_3$ - initial location coefficient $p_i$ - parameters yielding the best function value obtained by this particle $p_g$ - parameters yielding the best function value obtained by all particles $x_{init}$ - initial parameter values provided by user

Definition at line 127 of file itkInitializationBiasedParticleSwarmOptimizer.h.

The documentation for this class was generated from the following file:

itkInitializationBiasedParticleSwarmOptimizer.h

Public Types

Public Member Functions

Static Public Member Functions

Additional Inherited Members

Detailed Description

Member Typedef Documentation

◆ CoefficientType

◆ ConstPointer

◆ Pointer

◆ Self

◆ Superclass

Constructor & Destructor Documentation

◆ InitializationBiasedParticleSwarmOptimizer()

◆ ~InitializationBiasedParticleSwarmOptimizer()

Member Function Documentation

◆ CreateAnother()

◆ GetGlobalCoefficient()

◆ GetInertiaCoefficient()

◆ GetInitializationCoefficient()

◆ GetNameOfClass()

◆ GetPersonalCoefficient()

◆ New()

◆ PrintSelf()

◆ SetGlobalCoefficient()

◆ SetInertiaCoefficient()

◆ SetInitializationCoefficient()

◆ SetPersonalCoefficient()

◆ UpdateSwarm()

Member Data Documentation

◆ m_GlobalCoefficient

◆ m_InertiaCoefficient

◆ m_InitializationCoefficient

◆ m_PersonalCoefficient