Gradient-free Differential Evolution method. More...

#include <DifferentialEvolution.hpp>

Inheritance diagram for sgpp::optimization::optimizer::DifferentialEvolution:

Public Member Functions
void	clone (std::unique_ptr< UnconstrainedOptimizer > &clone) const override

	DifferentialEvolution (const base::ScalarFunction &f, size_t maxFcnEvalCount=DEFAULT_N, size_t populationSize=0, double crossoverProbability=DEFAULT_CROSSOVER_PROBABILITY, double scalingFactor=DEFAULT_SCALING_FACTOR, size_t idleGenerationsCount=DEFAULT_IDLE_GENERATIONS_COUNT, double avgImprovementThreshold=DEFAULT_AVG_IMPROVEMENT_THRESHOLD, double maxDistanceThreshold=DEFAULT_MAX_DISTANCE_THRESHOLD)
	Constructor.

	DifferentialEvolution (const DifferentialEvolution &other)
	Copy constructor.

double	getAvgImprovementThreshold () const

double	getCrossoverProbability () const

size_t	getIdleGenerationsCount () const

double	getMaxDistanceThreshold () const

size_t	getPopulationSize () const

double	getScalingFactor () const

void	optimize () override
	Pure virtual method for optimization of the objective function.

void	setAvgImprovementThreshold (double avgImprovementThreshold)

void	setCrossoverProbability (double crossoverProbability)

void	setIdleGenerationsCount (size_t idleGenerationsCount)

void	setMaxDistanceThreshold (double maxDistanceThreshold)

void	setPopulationSize (size_t populationSize)

void	setScalingFactor (double scalingFactor)

	~DifferentialEvolution () override
	Destructor.

Public Member Functions inherited from sgpp::optimization::optimizer::UnconstrainedOptimizer
const base::DataMatrix &	getHistoryOfOptimalPoints () const

const base::DataVector &	getHistoryOfOptimalValues () const

size_t	getN () const

base::ScalarFunction &	getObjectiveFunction () const

base::ScalarFunctionGradient *	getObjectiveGradient () const

base::ScalarFunctionHessian *	getObjectiveHessian () const

const base::DataVector &	getOptimalPoint () const

double	getOptimalValue () const

const base::DataVector &	getStartingPoint () const

void	setN (size_t N)

virtual void	setObjectiveFunction (const base::ScalarFunction &f)

virtual void	setObjectiveGradient (const base::ScalarFunctionGradient *fGradient)

virtual void	setObjectiveHessian (const base::ScalarFunctionHessian *fHessian)

void	setStartingPoint (const base::DataVector &startingPoint)

	UnconstrainedOptimizer (const base::ScalarFunction &f, const base::ScalarFunctionGradient fGradient, const base::ScalarFunctionHessian fHessian, size_t N=DEFAULT_N)
	Constructor.

	UnconstrainedOptimizer (const UnconstrainedOptimizer &other)
	Copy constructor.

virtual	~UnconstrainedOptimizer ()
	Destructor.

Static Public Attributes
static constexpr double	DEFAULT_AVG_IMPROVEMENT_THRESHOLD = 1e-6
	default stopping criterion parameter 2

static constexpr double	DEFAULT_CROSSOVER_PROBABILITY = 0.5
	default crossover probability

static const size_t	DEFAULT_IDLE_GENERATIONS_COUNT = 20
	default stopping criterion parameter 1

static constexpr double	DEFAULT_MAX_DISTANCE_THRESHOLD = 1e-4
	default stopping criterion parameter 3

static constexpr double	DEFAULT_SCALING_FACTOR = 0.6
	default crossover scaling factor

Static Public Attributes inherited from sgpp::optimization::optimizer::UnconstrainedOptimizer
static const size_t	DEFAULT_N = 1000
	default maximal number of iterations or function evaluations

Protected Attributes
double	avgImprovementThreshold
	stopping criterion parameter 2

double	crossoverProbability
	crossover probability

size_t	idleGenerationsCount
	stopping criterion parameter 1

double	maxDistanceThreshold
	stopping criterion parameter 3

size_t	populationSize
	number of individuals

double	scalingFactor
	crossover scaling factor

Protected Attributes inherited from sgpp::optimization::optimizer::UnconstrainedOptimizer
std::unique_ptr< base::ScalarFunction >	f
	objective function

std::unique_ptr< base::ScalarFunctionGradient >	fGradient
	objective function gradient

std::unique_ptr< base::ScalarFunctionHessian >	fHessian
	objective function Hessian

base::DataVector	fHist
	search history vector (optimal values)

double	fOpt
	result of optimization (optimal function value)

size_t	N
	maximal number of iterations or function evaluations

base::DataVector	x0
	starting point

base::DataMatrix	xHist
	search history matrix (optimal points)

base::DataVector	xOpt
	result of optimization (location of optimum)

Detailed Description

Gradient-free Differential Evolution method.

Constructor & Destructor Documentation

◆ DifferentialEvolution() [1/2]

sgpp::optimization::optimizer::DifferentialEvolution::DifferentialEvolution	(	const base::ScalarFunction &	f,
		size_t	maxFcnEvalCount = `DEFAULT_N`,
		size_t	populationSize = `0`,
		double	crossoverProbability = `DEFAULT_CROSSOVER_PROBABILITY`,
		double	scalingFactor = `DEFAULT_SCALING_FACTOR`,
		size_t	idleGenerationsCount = `DEFAULT_IDLE_GENERATIONS_COUNT`,
		double	avgImprovementThreshold = `DEFAULT_AVG_IMPROVEMENT_THRESHOLD`,
		double	maxDistanceThreshold = `DEFAULT_MAX_DISTANCE_THRESHOLD`
	)

Constructor.

Parameters

f	objective function
maxFcnEvalCount	maximal number of function evaluations
populationSize	number of individuals (default: \(10d\))
crossoverProbability	crossover probability
scalingFactor	crossover scaling factor
idleGenerationsCount	stopping criterion parameter 1
avgImprovementThreshold	stopping criterion parameter 2
maxDistanceThreshold	stopping criterion parameter 3

◆ DifferentialEvolution() [2/2]

sgpp::optimization::optimizer::DifferentialEvolution::DifferentialEvolution ( const DifferentialEvolution & other )

Copy constructor.

Parameters

other optimizer to be copied

◆ ~DifferentialEvolution()

sgpp::optimization::optimizer::DifferentialEvolution::~DifferentialEvolution ( )

override

Destructor.

Member Function Documentation

◆ clone()

void sgpp::optimization::optimizer::DifferentialEvolution::clone ( std::unique_ptr< UnconstrainedOptimizer > & clone ) const

overridevirtual

Parameters

[out] clone pointer to cloned object

Implements sgpp::optimization::optimizer::UnconstrainedOptimizer.

References clone().

Referenced by clone().

◆ getAvgImprovementThreshold()

double sgpp::optimization::optimizer::DifferentialEvolution::getAvgImprovementThreshold ( ) const

Returns: stopping criterion parameter 2

References avgImprovementThreshold.

◆ getCrossoverProbability()

double sgpp::optimization::optimizer::DifferentialEvolution::getCrossoverProbability ( ) const

Returns: crossover probability

References crossoverProbability.

◆ getIdleGenerationsCount()

size_t sgpp::optimization::optimizer::DifferentialEvolution::getIdleGenerationsCount ( ) const

Returns: stopping criterion parameter 1

References idleGenerationsCount.

◆ getMaxDistanceThreshold()

double sgpp::optimization::optimizer::DifferentialEvolution::getMaxDistanceThreshold ( ) const

Returns: stopping criterion parameter 3

References maxDistanceThreshold.

◆ getPopulationSize()

size_t sgpp::optimization::optimizer::DifferentialEvolution::getPopulationSize ( ) const

Returns: number of individuals

References populationSize.

◆ getScalingFactor()

double sgpp::optimization::optimizer::DifferentialEvolution::getScalingFactor ( ) const

Returns: crossover scaling factor

References scalingFactor.

◆ optimize()

void sgpp::optimization::optimizer::DifferentialEvolution::optimize ( )

overridevirtual

Pure virtual method for optimization of the objective function.

The result of the optimization process can be obtained by member functions, e.g., getOptimalPoint() and getOptimalValue().

Implements sgpp::optimization::optimizer::UnconstrainedOptimizer.

References sgpp::base::DataVector::append(), sgpp::base::DataMatrix::appendRow(), avgImprovementThreshold, sgpp::base::ScalarFunction::clone(), crossoverProbability, sgpp::base::ScalarFunction::eval(), sgpp::optimization::optimizer::UnconstrainedOptimizer::f, sgpp::optimization::optimizer::UnconstrainedOptimizer::fHist, sgpp::optimization::optimizer::UnconstrainedOptimizer::fOpt, sgpp::base::Printer::getInstance(), sgpp::base::RandomNumberGenerator::getInstance(), sgpp::base::RandomNumberGenerator::getUniformIndexRN(), sgpp::base::RandomNumberGenerator::getUniformRN(), idleGenerationsCount, maxDistanceThreshold, sgpp::optimization::optimizer::UnconstrainedOptimizer::N, populationSize, sgpp::base::Printer::printStatusBegin(), sgpp::base::Printer::printStatusEnd(), sgpp::base::Printer::printStatusUpdate(), sgpp::base::DataMatrix::resize(), scalingFactor, sgpp::optimization::optimizer::UnconstrainedOptimizer::xHist, and sgpp::optimization::optimizer::UnconstrainedOptimizer::xOpt.

◆ setAvgImprovementThreshold()

void sgpp::optimization::optimizer::DifferentialEvolution::setAvgImprovementThreshold ( double avgImprovementThreshold )

Parameters

avgImprovementThreshold stopping criterion parameter 2

References avgImprovementThreshold.

◆ setCrossoverProbability()

void sgpp::optimization::optimizer::DifferentialEvolution::setCrossoverProbability ( double crossoverProbability )

Parameters

crossoverProbability crossover probability

References crossoverProbability.

◆ setIdleGenerationsCount()

void sgpp::optimization::optimizer::DifferentialEvolution::setIdleGenerationsCount ( size_t idleGenerationsCount )

Parameters

idleGenerationsCount stopping criterion parameter 1

References idleGenerationsCount.

◆ setMaxDistanceThreshold()

void sgpp::optimization::optimizer::DifferentialEvolution::setMaxDistanceThreshold ( double maxDistanceThreshold )

Parameters

maxDistanceThreshold stopping criterion parameter 3

References maxDistanceThreshold.

◆ setPopulationSize()

void sgpp::optimization::optimizer::DifferentialEvolution::setPopulationSize ( size_t populationSize )

Parameters

populationSize number of individuals

References populationSize.

◆ setScalingFactor()

void sgpp::optimization::optimizer::DifferentialEvolution::setScalingFactor ( double scalingFactor )

Parameters

scalingFactor crossover scaling factor

References scalingFactor.

Member Data Documentation

◆ avgImprovementThreshold

double sgpp::optimization::optimizer::DifferentialEvolution::avgImprovementThreshold

protected

stopping criterion parameter 2

Referenced by getAvgImprovementThreshold(), optimize(), and setAvgImprovementThreshold().

◆ crossoverProbability

double sgpp::optimization::optimizer::DifferentialEvolution::crossoverProbability

protected

crossover probability

Referenced by getCrossoverProbability(), optimize(), and setCrossoverProbability().

◆ DEFAULT_AVG_IMPROVEMENT_THRESHOLD

constexpr double sgpp::optimization::optimizer::DifferentialEvolution::DEFAULT_AVG_IMPROVEMENT_THRESHOLD = 1e-6

staticconstexpr

default stopping criterion parameter 2

◆ DEFAULT_CROSSOVER_PROBABILITY

constexpr double sgpp::optimization::optimizer::DifferentialEvolution::DEFAULT_CROSSOVER_PROBABILITY = 0.5

staticconstexpr

default crossover probability

◆ DEFAULT_IDLE_GENERATIONS_COUNT

const size_t sgpp::optimization::optimizer::DifferentialEvolution::DEFAULT_IDLE_GENERATIONS_COUNT = 20

static

default stopping criterion parameter 1

◆ DEFAULT_MAX_DISTANCE_THRESHOLD

constexpr double sgpp::optimization::optimizer::DifferentialEvolution::DEFAULT_MAX_DISTANCE_THRESHOLD = 1e-4

staticconstexpr

default stopping criterion parameter 3

◆ DEFAULT_SCALING_FACTOR

constexpr double sgpp::optimization::optimizer::DifferentialEvolution::DEFAULT_SCALING_FACTOR = 0.6

staticconstexpr

default crossover scaling factor

◆ idleGenerationsCount

size_t sgpp::optimization::optimizer::DifferentialEvolution::idleGenerationsCount

protected

stopping criterion parameter 1

Referenced by getIdleGenerationsCount(), optimize(), and setIdleGenerationsCount().

◆ maxDistanceThreshold

double sgpp::optimization::optimizer::DifferentialEvolution::maxDistanceThreshold

protected

stopping criterion parameter 3

Referenced by getMaxDistanceThreshold(), optimize(), and setMaxDistanceThreshold().

◆ populationSize

size_t sgpp::optimization::optimizer::DifferentialEvolution::populationSize

protected

number of individuals

Referenced by getPopulationSize(), optimize(), and setPopulationSize().

◆ scalingFactor

double sgpp::optimization::optimizer::DifferentialEvolution::scalingFactor

protected

crossover scaling factor

Referenced by getScalingFactor(), optimize(), and setScalingFactor().

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

optimization/src/sgpp/optimization/optimizer/unconstrained/DifferentialEvolution.hpp
optimization/src/sgpp/optimization/optimizer/unconstrained/DifferentialEvolution.cpp

Public Member Functions

Static Public Attributes

Protected Attributes

Detailed Description

Constructor & Destructor Documentation

◆ DifferentialEvolution() [1/2]

◆ DifferentialEvolution() [2/2]

◆ ~DifferentialEvolution()

Member Function Documentation

◆ clone()

◆ getAvgImprovementThreshold()

◆ getCrossoverProbability()

◆ getIdleGenerationsCount()

◆ getMaxDistanceThreshold()

◆ getPopulationSize()

◆ getScalingFactor()

◆ optimize()

◆ setAvgImprovementThreshold()

◆ setCrossoverProbability()

◆ setIdleGenerationsCount()

◆ setMaxDistanceThreshold()

◆ setPopulationSize()

◆ setScalingFactor()

Member Data Documentation

◆ avgImprovementThreshold

◆ crossoverProbability

◆ DEFAULT_AVG_IMPROVEMENT_THRESHOLD

◆ DEFAULT_CROSSOVER_PROBABILITY

◆ DEFAULT_IDLE_GENERATIONS_COUNT

◆ DEFAULT_MAX_DISTANCE_THRESHOLD

◆ DEFAULT_SCALING_FACTOR

◆ idleGenerationsCount

◆ maxDistanceThreshold

◆ populationSize

◆ scalingFactor