sgpp::optimization::optimizer::LogBarrier Class Reference

Log Barrier method for constrained optimization. More...

#include <LogBarrier.hpp>

Inheritance diagram for sgpp::optimization::optimizer::LogBarrier:

Public Member Functions
void	clone (std::unique_ptr< UnconstrainedOptimizer > &clone) const override
double	getBarrierDecreaseFactor () const
double	getBarrierStartValue () const
const std::vector< size_t > &	getHistoryOfInnerIterationNumbers () const
const base::DataMatrix &	getHistoryOfInnerIterationPoints () const
double	getTolerance () const
	LogBarrier (const base::ScalarFunction &f, const base::ScalarFunctionGradient &fGradient, const base::VectorFunction &g, const base::VectorFunctionGradient &gGradient, size_t maxItCount=DEFAULT_N, double tolerance=DEFAULT_TOLERANCE, double barrierStartValue=DEFAULT_BARRIER_START_VALUE, double barrierDecreaseFactor=DEFAULT_BARRIER_DECREASE_FACTOR)
	Constructor with adaptive gradient descent as optimization algorithm (gradient-based).
	LogBarrier (const base::ScalarFunction &f, const base::VectorFunction &g, size_t maxItCount=DEFAULT_N, double tolerance=DEFAULT_TOLERANCE, double barrierStartValue=DEFAULT_BARRIER_START_VALUE, double barrierDecreaseFactor=DEFAULT_BARRIER_DECREASE_FACTOR)
	Constructor with Nelder-Mead as optimization algorithm (gradient-free).
	LogBarrier (const LogBarrier &other)
	Copy constructor.
	LogBarrier (const UnconstrainedOptimizer &unconstrainedOptimizer, const base::VectorFunction &g, const base::VectorFunctionGradient *gGradient, size_t maxItCount=DEFAULT_N, double tolerance=DEFAULT_TOLERANCE, double barrierStartValue=DEFAULT_BARRIER_START_VALUE, double barrierDecreaseFactor=DEFAULT_BARRIER_DECREASE_FACTOR)
	Constructor with custom unconstrained optimization algorithm (gradient-free or gradient-based).
void	optimize () override
	Pure virtual method for optimization of the objective function.
void	setBarrierDecreaseFactor (double barrierDecreaseFactor)
void	setBarrierStartValue (double barrierStartValue)
void	setTolerance (double tolerance)
	~LogBarrier () override
	Destructor.
Public Member Functions inherited from sgpp::optimization::optimizer::ConstrainedOptimizer
	ConstrainedOptimizer (const base::ScalarFunction &f, const base::ScalarFunctionGradient &fGradient, const base::VectorFunction &g, const base::VectorFunctionGradient &gGradient, const base::VectorFunction &h, const base::VectorFunctionGradient &hGradient, size_t N=DEFAULT_N)
	Constructor.
	ConstrainedOptimizer (const base::ScalarFunction &f, const base::VectorFunction &g, const base::VectorFunction &h, size_t N=DEFAULT_N)
	Constructor.
	ConstrainedOptimizer (const ConstrainedOptimizer &other)
	Copy constructor.
	ConstrainedOptimizer (const UnconstrainedOptimizer &unconstrainedOptimizer, const base::VectorFunction &g, const base::VectorFunctionGradient *gGradient, const base::VectorFunction &h, const base::VectorFunctionGradient *hGradient, size_t N=DEFAULT_N)
	Constructor with custom unconstrained optimization algorithm (gradient-free or gradient-based).
base::VectorFunction &	getEqualityConstraintFunction () const
base::VectorFunctionGradient *	getEqualityConstraintGradient () const
base::VectorFunction &	getInequalityConstraintFunction () const
base::VectorFunctionGradient *	getInequalityConstraintGradient () const
void	setEqualityConstraintFunction (const base::VectorFunction &h)
void	setEqualityConstraintGradient (const base::VectorFunctionGradient *hGradient)
void	setInequalityConstraintFunction (const base::VectorFunction &g)
void	setInequalityConstraintGradient (const base::VectorFunctionGradient *gGradient)
	~ConstrainedOptimizer () 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_BARRIER_DECREASE_FACTOR = 0.5
	default barrier decrease factor
static constexpr double	DEFAULT_BARRIER_START_VALUE = 1.0
	default barrier start value
static constexpr double	DEFAULT_TOLERANCE = 1e-6
	default tolerance
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
std::vector< size_t >	kHistInner
	search history (number of inner iterations)
double	mu0
	barrier start value
double	rhoMuMinus
	barrier decrease factor
double	theta
	tolerance
base::DataMatrix	xHistInner
	search history (inner iterations)
Protected Attributes inherited from sgpp::optimization::optimizer::ConstrainedOptimizer
std::unique_ptr< base::VectorFunction >	g
	inequality constraint function
std::unique_ptr< base::VectorFunctionGradient >	gGradient
	inequality constraint function gradient
std::unique_ptr< base::VectorFunction >	h
	equality constraint function
std::unique_ptr< base::VectorFunctionGradient >	hGradient
	equality constraint function gradient
std::unique_ptr< UnconstrainedOptimizer >	unconstrainedOptimizer
	unconstrained optimization algorithm
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

Log Barrier method for constrained optimization.

Constructor & Destructor Documentation

LogBarrier() [1/4]

sgpp::optimization::optimizer::LogBarrier::LogBarrier	(	const base::ScalarFunction &	f,
		const base::VectorFunction &	g,
		size_t	maxItCount = DEFAULT_N,
		double	tolerance = DEFAULT_TOLERANCE,
		double	barrierStartValue = DEFAULT_BARRIER_START_VALUE,
		double	barrierDecreaseFactor = DEFAULT_BARRIER_DECREASE_FACTOR
	)

Constructor with Nelder-Mead as optimization algorithm (gradient-free).

Parameters

f	objective function
g	inequality constraint
maxItCount	maximal number of function evaluations
tolerance	tolerance
barrierStartValue	barrier start value
barrierDecreaseFactor	barrier decrease factor

LogBarrier() [2/4]

sgpp::optimization::optimizer::LogBarrier::LogBarrier	(	const base::ScalarFunction &	f,
		const base::ScalarFunctionGradient &	fGradient,
		const base::VectorFunction &	g,
		const base::VectorFunctionGradient &	gGradient,
		size_t	maxItCount = DEFAULT_N,
		double	tolerance = DEFAULT_TOLERANCE,
		double	barrierStartValue = DEFAULT_BARRIER_START_VALUE,
		double	barrierDecreaseFactor = DEFAULT_BARRIER_DECREASE_FACTOR
	)

Constructor with adaptive gradient descent as optimization algorithm (gradient-based).

Parameters

f	objective function
fGradient	objective function gradient
g	inequality constraint
gGradient	inequality constraint gradient
maxItCount	maximal number of function evaluations
tolerance	tolerance
barrierStartValue	barrier start value
barrierDecreaseFactor	barrier decrease factor

References setTolerance(), theta, and sgpp::optimization::optimizer::ConstrainedOptimizer::unconstrainedOptimizer.

LogBarrier() [3/4]

sgpp::optimization::optimizer::LogBarrier::LogBarrier	(	const UnconstrainedOptimizer &	unconstrainedOptimizer,
		const base::VectorFunction &	g,
		const base::VectorFunctionGradient *	gGradient,
		size_t	maxItCount = DEFAULT_N,
		double	tolerance = DEFAULT_TOLERANCE,
		double	barrierStartValue = DEFAULT_BARRIER_START_VALUE,
		double	barrierDecreaseFactor = DEFAULT_BARRIER_DECREASE_FACTOR
	)

Constructor with custom unconstrained optimization algorithm (gradient-free or gradient-based).

Parameters

unconstrainedOptimizer	unconstrained optimization algorithm
g	inequality constraint
gGradient	inequality constraint gradient (nullptr to omit)
maxItCount	maximal number of function evaluations
tolerance	tolerance
barrierStartValue	barrier start value
barrierDecreaseFactor	barrier decrease factor

LogBarrier() [4/4]

sgpp::optimization::optimizer::LogBarrier::LogBarrier

(

const LogBarrier &

other

)

Copy constructor.

Parameters

other

optimizer to be copied

~LogBarrier()

sgpp::optimization::optimizer::LogBarrier::~LogBarrier ( )

override

Destructor.

Member Function Documentation

clone()

void sgpp::optimization::optimizer::LogBarrier::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().

getBarrierDecreaseFactor()

double sgpp::optimization::optimizer::LogBarrier::getBarrierDecreaseFactor

(

)

const

Returns

barrier decrease factor

References rhoMuMinus.

getBarrierStartValue()

double sgpp::optimization::optimizer::LogBarrier::getBarrierStartValue

(

)

const

Returns

barrier start value

References mu0.

getHistoryOfInnerIterationNumbers()

const std::vector< size_t > & sgpp::optimization::optimizer::LogBarrier::getHistoryOfInnerIterationNumbers

(

)

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 kHistInner.

getHistoryOfInnerIterationPoints()

const base::DataMatrix & sgpp::optimization::optimizer::LogBarrier::getHistoryOfInnerIterationPoints

(

)

const

Returns

tall matrix (d columns) in which the history of optimal points of the iterations are concatenated

References xHistInner.

getTolerance()

double sgpp::optimization::optimizer::LogBarrier::getTolerance

(

)

const

Returns

tolerance

References theta.

optimize()

void sgpp::optimization::optimizer::LogBarrier::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::f, sgpp::optimization::optimizer::UnconstrainedOptimizer::fGradient, sgpp::optimization::optimizer::UnconstrainedOptimizer::fHist, sgpp::optimization::optimizer::UnconstrainedOptimizer::fOpt, sgpp::optimization::optimizer::ConstrainedOptimizer::g, sgpp::base::Printer::getInstance(), sgpp::base::DataMatrix::getNrows(), sgpp::optimization::optimizer::ConstrainedOptimizer::gGradient, kHistInner, sgpp::base::DataVector::l2Norm(), mu, mu0, sgpp::optimization::optimizer::UnconstrainedOptimizer::N, sgpp::base::Printer::printStatusBegin(), sgpp::base::Printer::printStatusEnd(), sgpp::base::Printer::printStatusUpdate(), sgpp::base::DataMatrix::resize(), rhoMuMinus, sgpp::base::DataVector::sub(), theta, sgpp::base::DataVector::toString(), sgpp::optimization::optimizer::ConstrainedOptimizer::unconstrainedOptimizer, sgpp::optimization::optimizer::UnconstrainedOptimizer::x0, sgpp::optimization::optimizer::UnconstrainedOptimizer::xHist, xHistInner, and sgpp::optimization::optimizer::UnconstrainedOptimizer::xOpt.

setBarrierDecreaseFactor()

void sgpp::optimization::optimizer::LogBarrier::setBarrierDecreaseFactor

(

double

barrierDecreaseFactor

)

Parameters

barrierDecreaseFactor

barrier decrease factor

References rhoMuMinus.

setBarrierStartValue()

void sgpp::optimization::optimizer::LogBarrier::setBarrierStartValue

(

double

barrierStartValue

)

Parameters

barrierStartValue

barrier start value

References mu0.

setTolerance()

void sgpp::optimization::optimizer::LogBarrier::setTolerance

(

double

tolerance

)

Parameters

tolerance

tolerance

References theta.

Referenced by LogBarrier().

Member Data Documentation

DEFAULT_BARRIER_DECREASE_FACTOR

constexpr double sgpp::optimization::optimizer::LogBarrier::DEFAULT_BARRIER_DECREASE_FACTOR = 0.5

staticconstexpr

default barrier decrease factor

DEFAULT_BARRIER_START_VALUE

constexpr double sgpp::optimization::optimizer::LogBarrier::DEFAULT_BARRIER_START_VALUE = 1.0

staticconstexpr

default barrier start value

DEFAULT_TOLERANCE

constexpr double sgpp::optimization::optimizer::LogBarrier::DEFAULT_TOLERANCE = 1e-6

staticconstexpr

default tolerance

kHistInner

std::vector<size_t> sgpp::optimization::optimizer::LogBarrier::kHistInner

protected

search history (number of inner iterations)

Referenced by getHistoryOfInnerIterationNumbers(), and optimize().

mu0

double sgpp::optimization::optimizer::LogBarrier::mu0

protected

barrier start value

Referenced by getBarrierStartValue(), optimize(), and setBarrierStartValue().

rhoMuMinus

double sgpp::optimization::optimizer::LogBarrier::rhoMuMinus

protected

barrier decrease factor

Referenced by getBarrierDecreaseFactor(), optimize(), and setBarrierDecreaseFactor().

theta

double sgpp::optimization::optimizer::LogBarrier::theta

protected

tolerance

Referenced by getTolerance(), LogBarrier(), optimize(), and setTolerance().

xHistInner

base::DataMatrix sgpp::optimization::optimizer::LogBarrier::xHistInner

protected

search history (inner iterations)

Referenced by getHistoryOfInnerIterationPoints(), and optimize().

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

• optimization/src/sgpp/optimization/optimizer/constrained/LogBarrier.hpp
• optimization/src/sgpp/optimization/optimizer/constrained/LogBarrier.cpp