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/*=========================================================================
*
* Copyright NumFOCUS
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* https://www.apache.org/licenses/LICENSE-2.0.txt
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*=========================================================================*/
#ifndef itkParticleSwarmOptimizer_h
#define itkParticleSwarmOptimizer_h
#include "itkParticleSwarmOptimizerBase.h"
#include "ITKOptimizersExport.h"
namespace itk
{
/** \class ParticleSwarmOptimizer
* \brief Implementation of a Particle Swarm Optimization (PSO) algorithm.
*
* The PSO algorithm was originally presented in:<br>
* J. Kennedy, R. Eberhart, "Particle Swarm Optimization",
* Proc. IEEE Int. Neural Networks, 1995.<br>
*
* 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:<br>
* \f[v_i(t+1) = wv_i(t) + c_1u_1(p_i-x_i(t)) + c_2u_2(p_g-x_i(t))\f]
* \f[x_i(t+1) = clampToBounds(x_i(t) + v_i(t+1))\f]
*
* where \f$u_i\f$ are \f$~U(0,1)\f$ and \f$w,c_1,c_2\f$ 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 \f$g\f$ 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.
*
* \ingroup Numerics Optimizers
* \ingroup ITKOptimizers
*/
class ITKOptimizers_EXPORT ParticleSwarmOptimizer : public ParticleSwarmOptimizerBase
{
public:
ITK_DISALLOW_COPY_AND_MOVE(ParticleSwarmOptimizer);
/** Standard "Self" type alias. */
using Self = ParticleSwarmOptimizer;
using Superclass = ParticleSwarmOptimizerBase;
using Pointer = SmartPointer<Self>;
using ConstPointer = SmartPointer<const Self>;
/** Method for creation through the object factory. */
itkNewMacro(Self);
/** \see LightObject::GetNameOfClass() */
itkOverrideGetNameOfClassMacro(ParticleSwarmOptimizer);
/** 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
*/
itkSetMacro(InertiaCoefficient, double);
itkGetMacro(InertiaCoefficient, double);
itkSetMacro(PersonalCoefficient, double);
itkGetMacro(PersonalCoefficient, double);
itkSetMacro(GlobalCoefficient, double);
itkGetMacro(GlobalCoefficient, double);
protected:
ParticleSwarmOptimizer();
~ParticleSwarmOptimizer() override;
void
PrintSelf(std::ostream & os, Indent indent) const override;
void
UpdateSwarm() override;
private:
ParametersType::ValueType m_InertiaCoefficient{};
ParametersType::ValueType m_PersonalCoefficient{};
ParametersType::ValueType m_GlobalCoefficient{};
};
} // end namespace itk
#endif
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