Implementation of a Particle Swarm Optimization (PSO) algorithm. More...

#include <itkParticleSwarmOptimizer.h>

Inheritance diagram for itk::ParticleSwarmOptimizer:

Collaboration diagram for itk::ParticleSwarmOptimizer:

Public Types
typedef SmartPointer< const Self >	ConstPointer
typedef SmartPointer< Self >	Pointer
typedef ParticleSwarmOptimizer	Self
typedef ParticleSwarmOptimizerBase	Superclass
Public Member Functions
virtual ::itk::LightObject::Pointer	CreateAnother (void) const
virtual double	GetGlobalCoefficient ()
virtual double	GetInertiaCoefficient ()
virtual const char *	GetNameOfClass () const
virtual double	GetPersonalCoefficient ()
virtual void	SetGlobalCoefficient (double _arg)
virtual void	SetInertiaCoefficient (double _arg)
virtual void	SetPersonalCoefficient (double _arg)
Static Public Member Functions
static Pointer	New ()
Protected Member Functions
	ParticleSwarmOptimizer ()
void	PrintSelf (std::ostream &os, Indent indent) const
virtual void	UpdateSwarm ()
virtual	~ParticleSwarmOptimizer ()
Private Member Functions
void	operator= (const Self &)
	ParticleSwarmOptimizer (const Self &)
Private Attributes
ParametersType::ValueType	m_GlobalCoefficient
ParametersType::ValueType	m_InertiaCoefficient
ParametersType::ValueType	m_PersonalCoefficient

Detailed Description

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 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, and the location of the best function value the particles in its neighborhood previously encountered. In this implementation we use a global neighborhood with the following update equations:

$v_i(t+1) = wv_i(t) + c_1u_1(p_i-x_i(t)) + c_2u_2(p_g-x_i(t))$

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

where $u_i$ are $~U(0,1)$ and $w,c_1,c_2$ are user selected weights.

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. 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 59 of file itkParticleSwarmOptimizer.h.

Member Typedef Documentation

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

Reimplemented from itk::ParticleSwarmOptimizerBase.

Definition at line 67 of file itkParticleSwarmOptimizer.h.

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

Reimplemented from itk::ParticleSwarmOptimizerBase.

Definition at line 66 of file itkParticleSwarmOptimizer.h.

typedef ParticleSwarmOptimizer itk::ParticleSwarmOptimizer::Self

Standard "Self" typedef.

Reimplemented from itk::ParticleSwarmOptimizerBase.

Definition at line 64 of file itkParticleSwarmOptimizer.h.

typedef ParticleSwarmOptimizerBase itk::ParticleSwarmOptimizer::Superclass

Reimplemented from itk::ParticleSwarmOptimizerBase.

Definition at line 65 of file itkParticleSwarmOptimizer.h.

Constructor & Destructor Documentation

itk::ParticleSwarmOptimizer::ParticleSwarmOptimizer ( ) [protected]

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

itk::ParticleSwarmOptimizer::ParticleSwarmOptimizer ( const Self & ) [private]

Member Function Documentation

virtual::itk::LightObject::Pointer itk::ParticleSwarmOptimizer::CreateAnother ( void ) 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::SingleValuedNonLinearOptimizer.

virtual double itk::ParticleSwarmOptimizer::GetGlobalCoefficient ( ) [virtual]

virtual double itk::ParticleSwarmOptimizer::GetInertiaCoefficient ( ) [virtual]

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

Run-time type information (and related methods).

Reimplemented from itk::ParticleSwarmOptimizerBase.

virtual double itk::ParticleSwarmOptimizer::GetPersonalCoefficient ( ) [virtual]

static Pointer itk::ParticleSwarmOptimizer::New ( ) [static]

Method for creation through the object factory.

Reimplemented from itk::SingleValuedNonLinearOptimizer.

void itk::ParticleSwarmOptimizer::operator= ( const Self & ) [private]

Types inherited from the superclass

Reimplemented from itk::ParticleSwarmOptimizerBase.

void itk::ParticleSwarmOptimizer::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::ParticleSwarmOptimizerBase.

virtual void itk::ParticleSwarmOptimizer::SetGlobalCoefficient ( double _arg ) [virtual]

virtual void itk::ParticleSwarmOptimizer::SetInertiaCoefficient ( double _arg ) [virtual]

The Particle swarm optimizer uses the following update formula: 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)) x_i(t+1) = clampToBounds(x_i(t) + v_i(t+1)) where w - inertia constant c_1 - personal coefficient c_2 - global 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

virtual void itk::ParticleSwarmOptimizer::SetPersonalCoefficient ( double _arg ) [virtual]