Constrained optimization problem. More...

#include <Problem.hpp>

Public Member Functions
	Problem (ObjectiveFunction &objectiveFunction, Constraint &constraint, OpenMD::StatusFunction &statFunc, const DynamicVector< RealType > &initialValue=DynamicVector< RealType >())
	default constructor

void	reset ()

RealType	value (const DynamicVector< RealType > &x)
	call objective function computation and increment evaluation counter

void	gradient (DynamicVector< RealType > &grad_f, const DynamicVector< RealType > &x)
	call objective function gradient computation and increment

RealType	valueAndGradient (DynamicVector< RealType > &grad_f, const DynamicVector< RealType > &x)
	call objective function computation and it gradient

Constraint &	constraint () const
	Constraint.

ObjectiveFunction &	objectiveFunction () const
	Objective function.

void	setCurrentValue (const DynamicVector< RealType > &currentValue)

const DynamicVector< RealType > &	currentValue () const
	current value of the local minimum

void	setFunctionValue (RealType functionValue)

RealType	functionValue () const
	value of objective function

void	setGradientNormValue (RealType squaredNorm)

RealType	gradientNormValue () const
	value of objective function gradient norm

int	functionEvaluation () const
	number of evaluation of objective function

int	gradientEvaluation () const
	number of evaluation of objective function gradient

RealType	DotProduct (DynamicVector< RealType > &v1, DynamicVector< RealType > &v2)

RealType	computeGradientNormValue (DynamicVector< RealType > &grad_f)

Protected Attributes
ObjectiveFunction &	objectiveFunction_
	Unconstrained objective function.

Constraint &	constraint_
	Constraint.

DynamicVector< RealType >	currentValue_
	current value of the local minimum

RealType	functionValue_
	function and gradient norm values at the curentValue_ (i.e. the last step)

RealType	squaredNorm_

int	functionEvaluation_
	number of evaluation of objective function and its gradient

int	gradientEvaluation_

StatusFunction &	statusFunction_
	status function

Detailed Description

Constrained optimization problem.

Definition at line 37 of file Problem.hpp.

Constructor & Destructor Documentation

◆ Problem()

QuantLib::Problem::Problem	(	ObjectiveFunction &	objectiveFunction,
		Constraint &	constraint,
		OpenMD::StatusFunction &	statFunc,
		const DynamicVector< RealType > &	initialValue = DynamicVector<RealType>() )

inline

default constructor

Definition at line 40 of file Problem.hpp.

Member Function Documentation

◆ computeGradientNormValue()

RealType QuantLib::Problem::computeGradientNormValue ( DynamicVector< RealType > & grad_f )

Definition at line 12 of file Problem.cpp.

◆ constraint()

Constraint & QuantLib::Problem::constraint ( ) const

inline

Constraint.

Definition at line 65 of file Problem.hpp.

References constraint_.

Referenced by QuantLib::ArmijoLineSearch::operator()().

◆ currentValue()

const DynamicVector< RealType > & QuantLib::Problem::currentValue ( ) const

inline

current value of the local minimum

Definition at line 77 of file Problem.hpp.

References currentValue_.

Referenced by QuantLib::LineSearchBasedMethod::minimize(), and QuantLib::ArmijoLineSearch::operator()().

◆ DotProduct()

RealType QuantLib::Problem::DotProduct	(	DynamicVector< RealType > &	v1,
		DynamicVector< RealType > &	v2 )

Definition at line 6 of file Problem.cpp.

◆ functionEvaluation()

int QuantLib::Problem::functionEvaluation ( ) const

inline

number of evaluation of objective function

Definition at line 95 of file Problem.hpp.

References functionEvaluation_.

◆ functionValue()

RealType QuantLib::Problem::functionValue ( ) const

inline

value of objective function

Definition at line 86 of file Problem.hpp.

References functionValue_.

Referenced by QuantLib::LineSearchBasedMethod::minimize(), and QuantLib::ArmijoLineSearch::operator()().

◆ gradient()

void QuantLib::Problem::gradient	(	DynamicVector< RealType > &	grad_f,
		const DynamicVector< RealType > &	x )

inline

call objective function gradient computation and increment

Definition at line 130 of file Problem.hpp.

References QuantLib::ObjectiveFunction::gradient(), and objectiveFunction_.

Referenced by QuantLib::ArmijoLineSearch::operator()().

◆ gradientEvaluation()

int QuantLib::Problem::gradientEvaluation ( ) const

inline

number of evaluation of objective function gradient

Definition at line 98 of file Problem.hpp.

◆ gradientNormValue()

RealType QuantLib::Problem::gradientNormValue ( ) const

inline

value of objective function gradient norm

Definition at line 92 of file Problem.hpp.

Referenced by QuantLib::LineSearchBasedMethod::minimize(), and QuantLib::ArmijoLineSearch::operator()().

◆ objectiveFunction()

ObjectiveFunction & QuantLib::Problem::objectiveFunction ( ) const

inline

Objective function.

Definition at line 68 of file Problem.hpp.

References objectiveFunction_.

◆ reset()

void QuantLib::Problem::reset ( )

inline

Warning: it does not reset the current minumum to any initial value

Definition at line 146 of file Problem.hpp.

References functionEvaluation_, and functionValue_.

Referenced by QuantLib::LineSearchBasedMethod::minimize().

◆ setCurrentValue()

void QuantLib::Problem::setCurrentValue ( const DynamicVector< RealType > & currentValue )

inline

Definition at line 70 of file Problem.hpp.

◆ setFunctionValue()

void QuantLib::Problem::setFunctionValue ( RealType functionValue )

inline

Definition at line 81 of file Problem.hpp.

◆ setGradientNormValue()

void QuantLib::Problem::setGradientNormValue ( RealType squaredNorm )

inline

Definition at line 88 of file Problem.hpp.

◆ value()

RealType QuantLib::Problem::value ( const DynamicVector< RealType > & x )

inline

call objective function computation and increment evaluation counter

Definition at line 121 of file Problem.hpp.

References currentValue_, functionEvaluation_, functionValue_, objectiveFunction_, statusFunction_, and QuantLib::ObjectiveFunction::value().

Referenced by QuantLib::ArmijoLineSearch::operator()().

◆ valueAndGradient()

RealType QuantLib::Problem::valueAndGradient	(	DynamicVector< RealType > &	grad_f,
		const DynamicVector< RealType > &	x )

inline

call objective function computation and it gradient

Definition at line 136 of file Problem.hpp.

References currentValue_, functionEvaluation_, functionValue_, objectiveFunction_, statusFunction_, and QuantLib::ObjectiveFunction::valueAndGradient().

Referenced by QuantLib::LineSearchBasedMethod::minimize().

Member Data Documentation

◆ constraint_

Constraint& QuantLib::Problem::constraint_

protected

Constraint.

Definition at line 108 of file Problem.hpp.

Referenced by constraint().

◆ currentValue_

DynamicVector<RealType> QuantLib::Problem::currentValue_

protected

current value of the local minimum

Definition at line 110 of file Problem.hpp.

Referenced by currentValue(), value(), and valueAndGradient().

◆ functionEvaluation_

int QuantLib::Problem::functionEvaluation_

protected

number of evaluation of objective function and its gradient

Definition at line 115 of file Problem.hpp.

Referenced by functionEvaluation(), reset(), value(), and valueAndGradient().

◆ functionValue_

RealType QuantLib::Problem::functionValue_

protected

function and gradient norm values at the curentValue_ (i.e. the last step)

Definition at line 113 of file Problem.hpp.

Referenced by functionValue(), reset(), value(), and valueAndGradient().

◆ gradientEvaluation_

int QuantLib::Problem::gradientEvaluation_

protected

Definition at line 115 of file Problem.hpp.

◆ objectiveFunction_

ObjectiveFunction& QuantLib::Problem::objectiveFunction_

protected

Unconstrained objective function.

Definition at line 106 of file Problem.hpp.

Referenced by gradient(), objectiveFunction(), value(), and valueAndGradient().

◆ squaredNorm_

RealType QuantLib::Problem::squaredNorm_

protected

Definition at line 113 of file Problem.hpp.

◆ statusFunction_

StatusFunction& QuantLib::Problem::statusFunction_

protected

status function

Definition at line 117 of file Problem.hpp.

Referenced by value(), and valueAndGradient().

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

optimization/Problem.hpp
optimization/Problem.cpp

Public Member Functions

Protected Attributes

Detailed Description

Constructor & Destructor Documentation

◆ Problem()

Member Function Documentation

◆ computeGradientNormValue()

◆ constraint()

◆ currentValue()

◆ DotProduct()

◆ functionEvaluation()

◆ functionValue()

◆ gradient()

◆ gradientEvaluation()

◆ gradientNormValue()

◆ objectiveFunction()

◆ reset()

◆ setCurrentValue()

◆ setFunctionValue()

◆ setGradientNormValue()

◆ value()

◆ valueAndGradient()

Member Data Documentation

◆ constraint_

◆ currentValue_

◆ functionEvaluation_

◆ functionValue_

◆ gradientEvaluation_

◆ objectiveFunction_

◆ squaredNorm_

◆ statusFunction_