sgpp::optimization::optimizer::MultiStart Class Reference

Meta optimization algorithm calling local algorithm multiple times. More...

#include <MultiStart.hpp>

Inheritance diagram for sgpp::optimization::optimizer::MultiStart:

Public Member Functions
void	clone (std::unique_ptr< UnconstrainedOptimizer > &clone) const override
const std::vector< size_t > &	getHistoryOfInnerIterations () const
size_t	getPopulationSize () const
	MultiStart (const base::ScalarFunction &f, size_t maxFcnEvalCount=DEFAULT_MAX_FCN_EVAL_COUNT, size_t populationSize=0)
	Constructor.
	MultiStart (const MultiStart &other)
	Copy constructor.
	MultiStart (const UnconstrainedOptimizer &optimizer, size_t maxFcnEvalCount=DEFAULT_MAX_FCN_EVAL_COUNT, size_t populationSize=0)
	Constructor with custom optimization algorithm.
void	optimize () override
	Pure virtual method for optimization of the objective function.
void	setObjectiveFunction (const base::ScalarFunction &f) override
void	setObjectiveGradient (const base::ScalarFunctionGradient *fGradient) override
void	setObjectiveHessian (const base::ScalarFunctionHessian *fHessian) override
void	setPopulationSize (size_t populationSize)
	~MultiStart () 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)
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 const size_t	DEFAULT_MAX_FCN_EVAL_COUNT = 1000
	default maximal number of function evaluations
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 Member Functions
void	initialize (size_t populationSize)
	Initializes populationSize.

Protected Attributes
NelderMead	defaultOptimizer
	default optimization algorithm
std::vector< size_t >	kHist
	search history (inner iterations)
std::unique_ptr< UnconstrainedOptimizer >	optimizer
	optimization algorithm
size_t	populationSize
	number of individual points
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

Meta optimization algorithm calling local algorithm multiple times.

MultiStart generates a random population of a given number of starting points, and then runs a local optimization algorithm for each of the starting point. The best point wins.

Constructor & Destructor Documentation

MultiStart() [1/3]

sgpp::optimization::optimizer::MultiStart::MultiStart	(	const base::ScalarFunction &	f,
		size_t	maxFcnEvalCount = DEFAULT_MAX_FCN_EVAL_COUNT,
		size_t	populationSize = 0
	)

Constructor.

By default, Nelder-Mead is used as optimization algorithm.

Parameters

f	objective function
maxFcnEvalCount	maximal number of function evaluations
populationSize	number of individual points (default: \(\min(10d, 100)\))

References sgpp::optimization::optimizer::NelderMead::clone(), defaultOptimizer, initialize(), optimizer, and populationSize.

MultiStart() [2/3]

sgpp::optimization::optimizer::MultiStart::MultiStart	(	const UnconstrainedOptimizer &	optimizer,
		size_t	maxFcnEvalCount = DEFAULT_MAX_FCN_EVAL_COUNT,
		size_t	populationSize = 0
	)

Constructor with custom optimization algorithm.

The current values of the optimizer's N and starting point properties will not be used.

Parameters

optimizer	optimization algorithm and objective function
maxFcnEvalCount	maximal number of function evaluations
populationSize	number of individual points (default: \(\min(10d, 100)\))

References sgpp::optimization::optimizer::UnconstrainedOptimizer::clone(), initialize(), optimizer, and populationSize.

MultiStart() [3/3]

sgpp::optimization::optimizer::MultiStart::MultiStart

(

const MultiStart &

other

)

Copy constructor.

Parameters

other

optimizer to be copied

References initialize(), optimizer, and populationSize.

~MultiStart()

sgpp::optimization::optimizer::MultiStart::~MultiStart ( )

override

Destructor.

Member Function Documentation

clone()

void sgpp::optimization::optimizer::MultiStart::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(), and sgpp::optimization::FuzzyExtensionPrincipleViaOptimization::FuzzyExtensionPrincipleViaOptimization().

getHistoryOfInnerIterations()

const std::vector< size_t > & sgpp::optimization::optimizer::MultiStart::getHistoryOfInnerIterations

(

)

const

Returns

vector in which the k-th entry indicates the number of inner iterations in the k-th (outer) iteration, empty vector on error

References kHist.

getPopulationSize()

size_t sgpp::optimization::optimizer::MultiStart::getPopulationSize

(

)

const

Returns

number of individual points

References populationSize.

initialize()

void sgpp::optimization::optimizer::MultiStart::initialize ( size_t  populationSize )

protected

Initializes populationSize.

Parameters

populationSize

number of individual points (zero to use default value)

References sgpp::optimization::optimizer::UnconstrainedOptimizer::f, and populationSize.

Referenced by MultiStart(), MultiStart(), and MultiStart().

optimize()

void sgpp::optimization::optimizer::MultiStart::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(), sgpp::optimization::optimizer::UnconstrainedOptimizer::clone(), sgpp::base::Printer::disableStatusPrinting(), sgpp::base::Printer::enableStatusPrinting(), sgpp::optimization::optimizer::UnconstrainedOptimizer::f, sgpp::optimization::optimizer::UnconstrainedOptimizer::fHist, sgpp::optimization::optimizer::UnconstrainedOptimizer::fOpt, sgpp::optimization::optimizer::UnconstrainedOptimizer::getHistoryOfOptimalPoints(), sgpp::base::Printer::getInstance(), sgpp::base::RandomNumberGenerator::getInstance(), sgpp::base::Printer::getMutex(), sgpp::base::DataMatrix::getNrows(), sgpp::optimization::optimizer::UnconstrainedOptimizer::getOptimalPoint(), sgpp::optimization::optimizer::UnconstrainedOptimizer::getOptimalValue(), sgpp::base::RandomNumberGenerator::getUniformRN(), sgpp::base::Printer::isStatusPrintingEnabled(), kHist, sgpp::base::MutexType::lock(), sgpp::optimization::optimizer::UnconstrainedOptimizer::N, sgpp::optimization::optimizer::UnconstrainedOptimizer::optimize(), optimizer, populationSize, sgpp::base::Printer::printStatusBegin(), sgpp::base::Printer::printStatusEnd(), sgpp::base::Printer::printStatusUpdate(), sgpp::base::DataMatrix::resize(), sgpp::optimization::optimizer::UnconstrainedOptimizer::setN(), sgpp::optimization::optimizer::UnconstrainedOptimizer::setStartingPoint(), sgpp::base::MutexType::unlock(), sgpp::optimization::optimizer::UnconstrainedOptimizer::x0, sgpp::optimization::optimizer::UnconstrainedOptimizer::xHist, and sgpp::optimization::optimizer::UnconstrainedOptimizer::xOpt.

Referenced by sgpp::datadriven::BayesianOptimization::fitScales(), and sgpp::datadriven::BayesianOptimization::main().

setObjectiveFunction()

void sgpp::optimization::optimizer::MultiStart::setObjectiveFunction ( const base::ScalarFunction &  f )

overridevirtual

Parameters

f	objective function

Reimplemented from sgpp::optimization::optimizer::UnconstrainedOptimizer.

References sgpp::optimization::optimizer::UnconstrainedOptimizer::f, optimizer, and sgpp::optimization::optimizer::UnconstrainedOptimizer::setObjectiveFunction().

setObjectiveGradient()

void sgpp::optimization::optimizer::MultiStart::setObjectiveGradient ( const base::ScalarFunctionGradient *  fGradient )

overridevirtual

Parameters

fGradient

objective gradient

Reimplemented from sgpp::optimization::optimizer::UnconstrainedOptimizer.

References sgpp::optimization::optimizer::UnconstrainedOptimizer::fGradient, optimizer, and sgpp::optimization::optimizer::UnconstrainedOptimizer::setObjectiveGradient().

setObjectiveHessian()

void sgpp::optimization::optimizer::MultiStart::setObjectiveHessian ( const base::ScalarFunctionHessian *  fHessian )

overridevirtual

Parameters

fHessian

objective Hessian

Reimplemented from sgpp::optimization::optimizer::UnconstrainedOptimizer.

References sgpp::optimization::optimizer::UnconstrainedOptimizer::fHessian, optimizer, and sgpp::optimization::optimizer::UnconstrainedOptimizer::setObjectiveHessian().

setPopulationSize()

void sgpp::optimization::optimizer::MultiStart::setPopulationSize

(

size_t

populationSize

)

Parameters

populationSize

number of individual points

References populationSize.

Member Data Documentation

DEFAULT_MAX_FCN_EVAL_COUNT

const size_t sgpp::optimization::optimizer::MultiStart::DEFAULT_MAX_FCN_EVAL_COUNT = 1000

static

default maximal number of function evaluations

defaultOptimizer

NelderMead sgpp::optimization::optimizer::MultiStart::defaultOptimizer

protected

default optimization algorithm

Referenced by MultiStart().

kHist

std::vector<size_t> sgpp::optimization::optimizer::MultiStart::kHist

protected

search history (inner iterations)

Referenced by getHistoryOfInnerIterations(), and optimize().

optimizer

std::unique_ptr<UnconstrainedOptimizer> sgpp::optimization::optimizer::MultiStart::optimizer

protected

optimization algorithm

Referenced by MultiStart(), MultiStart(), MultiStart(), optimize(), setObjectiveFunction(), setObjectiveGradient(), and setObjectiveHessian().

populationSize

size_t sgpp::optimization::optimizer::MultiStart::populationSize

protected

number of individual points

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

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

• optimization/src/sgpp/optimization/optimizer/unconstrained/MultiStart.hpp
• optimization/src/sgpp/optimization/optimizer/unconstrained/MultiStart.cpp