/*========================================================================= * * 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:
* 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:
* \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; using ConstPointer = SmartPointer; /** 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