Abstract class for solving constrained optimization problems. More...

#include <ConstrainedOptimizer.hpp>

Inheritance diagram for sgpp::optimization::optimizer::ConstrainedOptimizer:

Public Member Functions
	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
virtual void	clone (std::unique_ptr< UnconstrainedOptimizer > &clone) const =0
	Pure virtual method for cloning the optimizer.

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

virtual void	optimize ()=0
	Pure virtual method for optimization of the objective function.

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.

Protected Attributes
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)

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

Detailed Description

Abstract class for solving constrained optimization problems.

Constructor & Destructor Documentation

◆ ConstrainedOptimizer() [1/4]

sgpp::optimization::optimizer::ConstrainedOptimizer::ConstrainedOptimizer	(	const base::ScalarFunction &	f,
		const base::VectorFunction &	g,
		const base::VectorFunction &	h,
		size_t	N = `DEFAULT_N`
	)

inline

Constructor.

By default, Nelder-Mead is used as optimization algorithm (gradient-free). The starting point is set to $(0.5, \dotsc, 0.5)^{\mathrm{T}}$. Depending on the implementation $g$ and/or $h$ may be ignored (if only equality or inequality constraints can be handled by the underlying algorithm).

Parameters

f	function to optimize
g	inequality constraint function ( $g(\vec{x}) \le 0$)
h	equality constraint function ( $h(\vec{x}) = 0$)
N	maximal number of iterations or objective function evaluations (depending on the implementation)

References sgpp::optimization::optimizer::UnconstrainedOptimizer::clone(), g, and h.

◆ ConstrainedOptimizer() [2/4]

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`
	)

inline

Constructor.

By default, adaptive gradient descent is used as optimization algorithm (gradient-based). The starting point is set to $(0.5, \dotsc, 0.5)^{\mathrm{T}}$. Depending on the implementation $g$ and/or $h$ may be ignored (if only equality or inequality constraints can be handled by the underlying algorithm).

Parameters

f	function to optimize
fGradient	gradient of f
g	inequality constraint function ( $g(\vec{x}) \le 0$)
gGradient	gradient of g
h	equality constraint function ( $h(\vec{x}) = 0$)
hGradient	gradient of h
N	maximal number of iterations or objective function evaluations (depending on the implementation)

References sgpp::optimization::optimizer::UnconstrainedOptimizer::clone(), g, gGradient, h, and hGradient.

◆ ConstrainedOptimizer() [3/4]

sgpp::optimization::optimizer::ConstrainedOptimizer::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`
	)

inline

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

The starting point is set to $(0.5, \dotsc, 0.5)^{\mathrm{T}}$. Depending on the implementation $g$ and/or $h$ may be ignored (if only equality or inequality constraints can be handled by the underlying algorithm).

Parameters

unconstrainedOptimizer	unconstrained optimizer
g	inequality constraint function ( $g(\vec{x}) \le 0$)
gGradient	gradient of g (nullptr to omit)
h	equality constraint function ( $h(\vec{x}) = 0$)
hGradient	gradient of h (nullptr to omit)
N	maximal number of iterations or objective function evaluations (depending on the implementation)

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

◆ ConstrainedOptimizer() [4/4]

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

inline

Copy constructor.

Parameters

other optimizer to be copied

◆ ~ConstrainedOptimizer()

sgpp::optimization::optimizer::ConstrainedOptimizer::~ConstrainedOptimizer ( )

inlineoverride

Destructor.

Member Function Documentation

◆ getEqualityConstraintFunction()

base::VectorFunction & sgpp::optimization::optimizer::ConstrainedOptimizer::getEqualityConstraintFunction ( ) const

inline

Returns: equality constraint function

References h.

◆ getEqualityConstraintGradient()

base::VectorFunctionGradient * sgpp::optimization::optimizer::ConstrainedOptimizer::getEqualityConstraintGradient ( ) const

inline

Returns: equality constraint function gradient

References hGradient.

◆ getInequalityConstraintFunction()

base::VectorFunction & sgpp::optimization::optimizer::ConstrainedOptimizer::getInequalityConstraintFunction ( ) const

inline

Returns: inequality constraint function

References g.

◆ getInequalityConstraintGradient()

base::VectorFunctionGradient * sgpp::optimization::optimizer::ConstrainedOptimizer::getInequalityConstraintGradient ( ) const

inline

Returns: inequality constraint function gradient

References gGradient.

◆ setEqualityConstraintFunction()

void sgpp::optimization::optimizer::ConstrainedOptimizer::setEqualityConstraintFunction ( const base::VectorFunction & h )

inline

Parameters

h	equality constraint function

References h.

◆ setEqualityConstraintGradient()

void sgpp::optimization::optimizer::ConstrainedOptimizer::setEqualityConstraintGradient ( const base::VectorFunctionGradient * hGradient )

inline

Parameters

hGradient equality constraint function gradient

References hGradient.

◆ setInequalityConstraintFunction()

void sgpp::optimization::optimizer::ConstrainedOptimizer::setInequalityConstraintFunction ( const base::VectorFunction & g )

inline

Parameters

g	inequality constraint function

References g.

◆ setInequalityConstraintGradient()

void sgpp::optimization::optimizer::ConstrainedOptimizer::setInequalityConstraintGradient ( const base::VectorFunctionGradient * gGradient )

inline

Parameters

gGradient inequality constraint function gradient

References gGradient.

Member Data Documentation

◆ g

std::unique_ptr<base::VectorFunction> sgpp::optimization::optimizer::ConstrainedOptimizer::g

protected

inequality constraint function

Referenced by ConstrainedOptimizer(), ConstrainedOptimizer(), sgpp::optimization::optimizer::AugmentedLagrangian::findFeasiblePoint(), getInequalityConstraintFunction(), sgpp::optimization::optimizer::AugmentedLagrangian::optimize(), sgpp::optimization::optimizer::LogBarrier::optimize(), sgpp::optimization::optimizer::SquaredPenalty::optimize(), and setInequalityConstraintFunction().

◆ gGradient

std::unique_ptr<base::VectorFunctionGradient> sgpp::optimization::optimizer::ConstrainedOptimizer::gGradient

protected

inequality constraint function gradient

Referenced by ConstrainedOptimizer(), sgpp::optimization::optimizer::AugmentedLagrangian::findFeasiblePoint(), getInequalityConstraintGradient(), sgpp::optimization::optimizer::AugmentedLagrangian::optimize(), sgpp::optimization::optimizer::LogBarrier::optimize(), sgpp::optimization::optimizer::SquaredPenalty::optimize(), and setInequalityConstraintGradient().

◆ h

std::unique_ptr<base::VectorFunction> sgpp::optimization::optimizer::ConstrainedOptimizer::h

protected

equality constraint function

Referenced by ConstrainedOptimizer(), ConstrainedOptimizer(), sgpp::optimization::optimizer::AugmentedLagrangian::findFeasiblePoint(), getEqualityConstraintFunction(), sgpp::optimization::optimizer::AugmentedLagrangian::optimize(), sgpp::optimization::optimizer::SquaredPenalty::optimize(), and setEqualityConstraintFunction().

◆ hGradient

std::unique_ptr<base::VectorFunctionGradient> sgpp::optimization::optimizer::ConstrainedOptimizer::hGradient

protected

equality constraint function gradient

Referenced by ConstrainedOptimizer(), sgpp::optimization::optimizer::AugmentedLagrangian::findFeasiblePoint(), getEqualityConstraintGradient(), sgpp::optimization::optimizer::AugmentedLagrangian::optimize(), sgpp::optimization::optimizer::SquaredPenalty::optimize(), and setEqualityConstraintGradient().

◆ unconstrainedOptimizer

std::unique_ptr<UnconstrainedOptimizer> sgpp::optimization::optimizer::ConstrainedOptimizer::unconstrainedOptimizer

protected

unconstrained optimization algorithm

Referenced by sgpp::optimization::optimizer::AugmentedLagrangian::AugmentedLagrangian(), ConstrainedOptimizer(), sgpp::optimization::optimizer::LogBarrier::LogBarrier(), sgpp::optimization::optimizer::AugmentedLagrangian::optimize(), sgpp::optimization::optimizer::LogBarrier::optimize(), sgpp::optimization::optimizer::SquaredPenalty::optimize(), and sgpp::optimization::optimizer::SquaredPenalty::SquaredPenalty().

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

optimization/src/sgpp/optimization/optimizer/constrained/ConstrainedOptimizer.hpp

f	function to optimize
g	inequality constraint function ( \(g(\vec{x}) \le 0\))
h	equality constraint function ( \(h(\vec{x}) = 0\))
N	maximal number of iterations or objective function evaluations (depending on the implementation)

Public Member Functions

Protected Attributes

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ ConstrainedOptimizer() [1/4]

◆ ConstrainedOptimizer() [2/4]

◆ ConstrainedOptimizer() [3/4]

◆ ConstrainedOptimizer() [4/4]

◆ ~ConstrainedOptimizer()

Member Function Documentation

◆ getEqualityConstraintFunction()

◆ getEqualityConstraintGradient()

◆ getInequalityConstraintFunction()

◆ getInequalityConstraintGradient()

◆ setEqualityConstraintFunction()

◆ setEqualityConstraintGradient()

◆ setInequalityConstraintFunction()

◆ setInequalityConstraintGradient()

Member Data Documentation

◆ g

◆ gGradient

◆ h

◆ hGradient

◆ unconstrainedOptimizer