ITK  4.1.0
Insight Segmentation and Registration Toolkit
Public Types | Public Member Functions | Static Public Member Functions | Protected Member Functions | Private Member Functions | Private Attributes
itk::ParticleSwarmOptimizer Class Reference

#include <itkParticleSwarmOptimizer.h>

+ Inheritance diagram for itk::ParticleSwarmOptimizer:
+ Collaboration diagram for itk::ParticleSwarmOptimizer:

List of all members.

Public Types

typedef SmartPointer< const SelfConstPointer
typedef SmartPointer< SelfPointer
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

Reimplemented from itk::ParticleSwarmOptimizerBase.

Definition at line 67 of file itkParticleSwarmOptimizer.h.

Reimplemented from itk::ParticleSwarmOptimizerBase.

Definition at line 66 of file itkParticleSwarmOptimizer.h.

Standard "Self" typedef.

Reimplemented from itk::ParticleSwarmOptimizerBase.

Definition at line 64 of file itkParticleSwarmOptimizer.h.

Reimplemented from itk::ParticleSwarmOptimizerBase.

Definition at line 65 of file itkParticleSwarmOptimizer.h.


Constructor & Destructor Documentation

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

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

Run-time type information (and related methods).

Reimplemented from itk::ParticleSwarmOptimizerBase.

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]
virtual void itk::ParticleSwarmOptimizer::UpdateSwarm ( ) [protected, virtual]

Implement your update rule in this function.

Implements itk::ParticleSwarmOptimizerBase.


Member Data Documentation

Definition at line 106 of file itkParticleSwarmOptimizer.h.

Definition at line 104 of file itkParticleSwarmOptimizer.h.

Definition at line 105 of file itkParticleSwarmOptimizer.h.


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