ROL
ROL::BoundConstraint< Real > Class Template Reference

Provides the interface to apply upper and lower bound constraints. More...

#include <ROL_BoundConstraint.hpp>

+ Inheritance diagram for ROL::BoundConstraint< Real >:

Public Member Functions

virtual ~BoundConstraint ()
 
 BoundConstraint (void)
 
 BoundConstraint (const Vector< Real > &x)
 
virtual void project (Vector< Real > &x)
 Project optimization variables onto the bounds.
 
virtual void projectInterior (Vector< Real > &x)
 Project optimization variables into the interior of the feasible set.
 
virtual void pruneUpperActive (Vector< Real > &v, const Vector< Real > &x, Real eps=Real(0))
 Set variables to zero if they correspond to the upper \(\epsilon\)-active set.
 
virtual void pruneUpperActive (Vector< Real > &v, const Vector< Real > &g, const Vector< Real > &x, Real xeps=Real(0), Real geps=Real(0))
 Set variables to zero if they correspond to the upper \(\epsilon\)-binding set.
 
virtual void pruneLowerActive (Vector< Real > &v, const Vector< Real > &x, Real eps=Real(0))
 Set variables to zero if they correspond to the lower \(\epsilon\)-active set.
 
virtual void pruneLowerActive (Vector< Real > &v, const Vector< Real > &g, const Vector< Real > &x, Real xeps=Real(0), Real geps=Real(0))
 Set variables to zero if they correspond to the \(\epsilon\)-binding set.
 
virtual const Ptr< const Vector< Real > > getLowerBound (void) const
 Return the ref count pointer to the lower bound vector.
 
virtual const Ptr< const Vector< Real > > getUpperBound (void) const
 Return the ref count pointer to the upper bound vector.
 
virtual bool isFeasible (const Vector< Real > &v)
 Check if the vector, v, is feasible.
 
virtual void applyInverseScalingFunction (Vector< Real > &dv, const Vector< Real > &v, const Vector< Real > &x, const Vector< Real > &g) const
 Apply inverse scaling function.
 
virtual void applyScalingFunctionJacobian (Vector< Real > &dv, const Vector< Real > &v, const Vector< Real > &x, const Vector< Real > &g) const
 Apply scaling function Jacobian.
 
void activateLower (void)
 Turn on lower bound.
 
void activateUpper (void)
 Turn on upper bound.
 
void activate (void)
 Turn on bounds.
 
void deactivateLower (void)
 Turn off lower bound.
 
void deactivateUpper (void)
 Turn off upper bound.
 
void deactivate (void)
 Turn off bounds.
 
bool isLowerActivated (void) const
 Check if lower bound are on.
 
bool isUpperActivated (void) const
 Check if upper bound are on.
 
bool isActivated (void) const
 Check if bounds are on.
 
void pruneActive (Vector< Real > &v, const Vector< Real > &x, Real eps=Real(0))
 Set variables to zero if they correspond to the \(\epsilon\)-active set.
 
void pruneActive (Vector< Real > &v, const Vector< Real > &g, const Vector< Real > &x, Real xeps=Real(0), Real geps=Real(0))
 Set variables to zero if they correspond to the \(\epsilon\)-binding set.
 
void pruneLowerInactive (Vector< Real > &v, const Vector< Real > &x, Real eps=Real(0))
 Set variables to zero if they correspond to the \(\epsilon\)-inactive set.
 
void pruneUpperInactive (Vector< Real > &v, const Vector< Real > &x, Real eps=Real(0))
 Set variables to zero if they correspond to the \(\epsilon\)-inactive set.
 
void pruneLowerInactive (Vector< Real > &v, const Vector< Real > &g, const Vector< Real > &x, Real xeps=Real(0), Real geps=Real(0))
 Set variables to zero if they correspond to the \(\epsilon\)-nonbinding set.
 
void pruneUpperInactive (Vector< Real > &v, const Vector< Real > &g, const Vector< Real > &x, Real xeps=Real(0), Real geps=Real(0))
 Set variables to zero if they correspond to the \(\epsilon\)-nonbinding set.
 
void pruneInactive (Vector< Real > &v, const Vector< Real > &x, Real eps=Real(0))
 Set variables to zero if they correspond to the \(\epsilon\)-inactive set.
 
void pruneInactive (Vector< Real > &v, const Vector< Real > &g, const Vector< Real > &x, Real xeps=Real(0), Real geps=Real(0))
 Set variables to zero if they correspond to the \(\epsilon\)-nonbinding set.
 
void computeProjectedGradient (Vector< Real > &g, const Vector< Real > &x)
 Compute projected gradient.
 
void computeProjectedStep (Vector< Real > &v, const Vector< Real > &x)
 Compute projected step.
 

Protected Member Functions

Real computeInf (const Vector< Real > &x) const
 

Protected Attributes

Ptr< Vector< Real > > lower_
 
Ptr< Vector< Real > > upper_
 

Private Attributes

bool Lactivated_
 Flag that determines whether or not the lower bounds are being used.
 
bool Uactivated_
 Flag that determines whether or not the upper bounds are being used.
 

Detailed Description

template<typename Real>
class ROL::BoundConstraint< Real >

Provides the interface to apply upper and lower bound constraints.

ROL's bound constraint class is to designed to handle point wise bound constraints on optimization variables. That is, let \(\mathcal{X}\) be a Banach space of functions from \(\Xi\) into \(\mathbb{R}\) (for example, \(\Xi\subset\mathbb{R}^d\) for some positive integer \(d\) and \(\mathcal{X}=L^2(\Xi)\) or \(\Xi = \{1,\ldots,n\}\) and \(\mathcal{X}=\mathbb{R}^n\)). For any \(x\in\mathcal{X}\), we consider bounds of the form

\[ a(\xi) \le x(\xi) \le b(\xi) \quad \text{for almost every }\xi\in\Xi. \]

Here, \(a(\xi)\le b(\xi)\) for almost every \(\xi\in\Xi\) and \(a,b\in \mathcal{X}\).

Definition at line 73 of file ROL_BoundConstraint.hpp.

Constructor & Destructor Documentation

◆ ~BoundConstraint()

template<typename Real>
virtual ROL::BoundConstraint< Real >::~BoundConstraint ( )
inlinevirtual

Definition at line 86 of file ROL_BoundConstraint.hpp.

◆ BoundConstraint() [1/2]

template<typename Real>
ROL::BoundConstraint< Real >::BoundConstraint ( void )

◆ BoundConstraint() [2/2]

template<typename Real>
ROL::BoundConstraint< Real >::BoundConstraint ( const Vector< Real > & x)

Member Function Documentation

◆ computeInf()

◆ project()

template<typename Real>
virtual void ROL::BoundConstraint< Real >::project ( Vector< Real > & x)
virtual

Project optimization variables onto the bounds.

This function implements the projection of \(x\) onto the bounds, i.e.,

\[ (P_{[a,b]}(x))(\xi) = \min\{b(\xi),\max\{a(\xi),x(\xi)\}\} \quad \text{for almost every }\xi\in\Xi. \]

Parameters
[in,out]xis the optimization variable.

Reimplemented in BoundConstraint_BurgersControl< Real >, H1BoundConstraint< Real >, H1BoundConstraint< Real >, H1BoundConstraint< Real >, L2BoundConstraint< Real >, L2BoundConstraint< Real >, and L2BoundConstraint< Real >.

Referenced by ROL::LineSearchStep< Real >::compute(), ROL::PrimalDualActiveSetStep< Real >::compute(), ROL::PrimalDualActiveSetStep< Real >::computeCriticalityMeasure(), ROL::TrustRegionStep< Real >::computeCriticalityMeasure(), ROL::AugmentedLagrangianStep< Real >::computeGradient(), ROL::FletcherStep< Real >::computeProjGradientNorm(), ROL::LineSearchStep< Real >::GradDotStep(), ROL::AugmentedLagrangianStep< Real >::initialize(), ROL::MoreauYosidaPenaltyStep< Real >::initialize(), ROL::MoreauYosidaPenaltyStep< Real >::initialize(), ROL::PrimalDualActiveSetStep< Real >::initialize(), ROL::Step< Real >::initialize(), ROL::TrustRegionStep< Real >::initialize(), ROL::TypeB::KelleySachsAlgorithm< Real >::initialize(), ROL::TypeB::KelleySachsAlgorithm< Real >::run(), ROL::TypeB::PrimalDualActiveSetAlgorithm< Real >::run(), ROL::InteriorPointStep< Real >::update(), ROL::InteriorPointStep< Real >::update(), ROL::ProjectedNewtonKrylovStep< Real >::update(), ROL::ProjectedNewtonStep< Real >::update(), ROL::ProjectedSecantStep< Real >::update(), ROL::TrustRegion< Real >::update(), and ROL::LineSearch< Real >::updateIterate().

◆ projectInterior()

template<typename Real>
virtual void ROL::BoundConstraint< Real >::projectInterior ( Vector< Real > & x)
virtual

Project optimization variables into the interior of the feasible set.

This function implements the projection of \(x\) into the interior of the feasible set, i.e.,

\[ (\bar{P}_{[a,b]}(x))(\xi) \in (a(\xi),b(\xi)) \quad \text{for almost every }\xi\in\Xi. \]

Parameters
[in,out]xis the optimization variable.

Referenced by ROL::InteriorPointStep< Real >::initialize(), ROL::InteriorPointStep< Real >::initialize(), ROL::TrustRegionStep< Real >::initialize(), ROL::TypeB::InteriorPointAlgorithm< Real >::initialize(), and ROL::TypeG::InteriorPointAlgorithm< Real >::initialize().

◆ pruneUpperActive() [1/2]

template<typename Real>
virtual void ROL::BoundConstraint< Real >::pruneUpperActive ( Vector< Real > & v,
const Vector< Real > & x,
Real eps = Real(0) )
virtual

Set variables to zero if they correspond to the upper \(\epsilon\)-active set.

This function sets \(v(\xi)=0\) if \(\xi\in\mathcal{A}^+_\epsilon(x)\). Here, the upper \(\epsilon\)-active set is defined as

\[ \mathcal{A}^+_\epsilon(x) = \{\,\xi\in\Xi\,:\,x(\xi) \ge b(\xi)-\epsilon\,\}. \]

Parameters
[out]vis the variable to be pruned.
[in]xis the current optimization variable.
[in]epsis the active-set tolerance \(\epsilon\).

Reimplemented in BoundConstraint_BurgersControl< Real >, H1BoundConstraint< Real >, H1BoundConstraint< Real >, H1BoundConstraint< Real >, L2BoundConstraint< Real >, L2BoundConstraint< Real >, and L2BoundConstraint< Real >.

Referenced by ROL::PrimalDualActiveSetStep< Real >::compute().

◆ pruneUpperActive() [2/2]

template<typename Real>
virtual void ROL::BoundConstraint< Real >::pruneUpperActive ( Vector< Real > & v,
const Vector< Real > & g,
const Vector< Real > & x,
Real xeps = Real(0),
Real geps = Real(0) )
virtual

Set variables to zero if they correspond to the upper \(\epsilon\)-binding set.

This function sets \(v(\xi)=0\) if \(\xi\in\mathcal{B}^+_\epsilon(x)\). Here, the upper \(\epsilon\)-binding set is defined as

\[ \mathcal{B}^+_\epsilon(x) = \{\,\xi\in\Xi\,:\,x(\xi) \ge b(\xi)-\epsilon_x,\; g(\xi) < -\epsilon_g \,\}. \]

Parameters
[out]vis the variable to be pruned.
[in]gis the negative search direction.
[in]xis the current optimization variable.
[in]xepsis the active-set tolerance \(\epsilon_x\).
[in]gepsis the binding-set tolerance \(\epsilon_g\).

Reimplemented in BoundConstraint_BurgersControl< Real >, H1BoundConstraint< Real >, H1BoundConstraint< Real >, H1BoundConstraint< Real >, L2BoundConstraint< Real >, L2BoundConstraint< Real >, and L2BoundConstraint< Real >.

◆ pruneLowerActive() [1/2]

template<typename Real>
virtual void ROL::BoundConstraint< Real >::pruneLowerActive ( Vector< Real > & v,
const Vector< Real > & x,
Real eps = Real(0) )
virtual

Set variables to zero if they correspond to the lower \(\epsilon\)-active set.

This function sets \(v(\xi)=0\) if \(\xi\in\mathcal{A}^-_\epsilon(x)\). Here, the lower \(\epsilon\)-active set is defined as

\[ \mathcal{A}^-_\epsilon(x) = \{\,\xi\in\Xi\,:\,x(\xi) \le a(\xi)+\epsilon\,\}. \]

Parameters
[out]vis the variable to be pruned.
[in]xis the current optimization variable.
[in]epsis the active-set tolerance \(\epsilon\).

Reimplemented in BoundConstraint_BurgersControl< Real >, H1BoundConstraint< Real >, H1BoundConstraint< Real >, H1BoundConstraint< Real >, L2BoundConstraint< Real >, L2BoundConstraint< Real >, and L2BoundConstraint< Real >.

Referenced by ROL::PrimalDualActiveSetStep< Real >::compute().

◆ pruneLowerActive() [2/2]

template<typename Real>
virtual void ROL::BoundConstraint< Real >::pruneLowerActive ( Vector< Real > & v,
const Vector< Real > & g,
const Vector< Real > & x,
Real xeps = Real(0),
Real geps = Real(0) )
virtual

Set variables to zero if they correspond to the \(\epsilon\)-binding set.

This function sets \(v(\xi)=0\) if \(\xi\in\mathcal{B}^-_\epsilon(x)\). Here, the lower \(\epsilon\)-binding set is defined as

\[ \mathcal{B}^-_\epsilon(x) = \{\,\xi\in\Xi\,:\,x(\xi) \le a(\xi)+\epsilon,\; g(\xi) > 0 \,\}. \]

Parameters
[out]vis the variable to be pruned.
[in]gis the negative search direction.
[in]xis the current optimization variable.
[in]xepsis the active-set tolerance \(\epsilon_x\).
[in]gepsis the binding-set tolerance \(\epsilon_g\).

Reimplemented in BoundConstraint_BurgersControl< Real >, H1BoundConstraint< Real >, H1BoundConstraint< Real >, H1BoundConstraint< Real >, L2BoundConstraint< Real >, L2BoundConstraint< Real >, and L2BoundConstraint< Real >.

◆ getLowerBound()

◆ getUpperBound()

◆ isFeasible()

template<typename Real>
virtual bool ROL::BoundConstraint< Real >::isFeasible ( const Vector< Real > & v)
virtual

◆ applyInverseScalingFunction()

template<typename Real>
virtual void ROL::BoundConstraint< Real >::applyInverseScalingFunction ( Vector< Real > & dv,
const Vector< Real > & v,
const Vector< Real > & x,
const Vector< Real > & g ) const
virtual

Apply inverse scaling function.

This function applies the inverse scaling function \(d(x,g)\) to a vector \(v\), i.e., the output is \(\mathrm{diag}(d(x,g)^{-1})v\). The scaling function must satisfy: (i) \(d(x,g)_i = 0\) if \(x_i = a_i\) and \(g_i \ge 0\); (ii) \(d(x,g)_i = 0\) if \(x_i = b_i\) and \(g_i \le 0\); and (iii) \(d(x,g)_i > 0\) otherwise.

Parameters
[out]dvis the inverse scaling function applied to v.
[in]vis the vector being scaled.
[in]xis the primal vector at which the scaling function is evaluated.
[in]gis the dual vector at which the scaling function is evaluated.

Referenced by ROL::TypeB::ColemanLiAlgorithm< Real >::applyC().

◆ applyScalingFunctionJacobian()

template<typename Real>
virtual void ROL::BoundConstraint< Real >::applyScalingFunctionJacobian ( Vector< Real > & dv,
const Vector< Real > & v,
const Vector< Real > & x,
const Vector< Real > & g ) const
virtual

Apply scaling function Jacobian.

This function applies the Jacobian of the scaling function \(d(x,g)\) to a vector \(v\). The output is \(\mathrm{diag}(d_x(x,g)g)v\). The scaling function must satisfy: (i) \(d(x,g)_i = 0\) if \(x_i = a_i\) and \(g_i \ge 0\); (ii) \(d(x,g)_i = 0\) if \(x_i = b_i\) and \(g_i \le 0\); and (iii) \(d(x,g)_i > 0\) otherwise.

Parameters
[out]dvis the scaling function Jacobian applied to v.
[in]vis the vector being scaled.
[in]xis the primal vector at which the scaling function is evaluated.
[in]gis the dual vector at which the scaling function is evaluated.

Referenced by ROL::TypeB::ColemanLiAlgorithm< Real >::applyC().

◆ activateLower()

template<typename Real>
void ROL::BoundConstraint< Real >::activateLower ( void )

Turn on lower bound.

This function turns on lower bounds.

Referenced by ROL::Bounds< Real >::Bounds(), and ROL::StdBoundConstraint< Real >::StdBoundConstraint().

◆ activateUpper()

template<typename Real>
void ROL::BoundConstraint< Real >::activateUpper ( void )

Turn on upper bound.

This function turns on upper bounds.

Referenced by ROL::Bounds< Real >::Bounds(), and ROL::StdBoundConstraint< Real >::StdBoundConstraint().

◆ activate()

◆ deactivateLower()

template<typename Real>
void ROL::BoundConstraint< Real >::deactivateLower ( void )

Turn off lower bound.

This function turns the lower bounds off.

◆ deactivateUpper()

template<typename Real>
void ROL::BoundConstraint< Real >::deactivateUpper ( void )

Turn off upper bound.

This function turns the upper bounds off.

◆ deactivate()

◆ isLowerActivated()

◆ isUpperActivated()

◆ isActivated()

◆ pruneActive() [1/2]

template<typename Real>
void ROL::BoundConstraint< Real >::pruneActive ( Vector< Real > & v,
const Vector< Real > & x,
Real eps = Real(0) )

◆ pruneActive() [2/2]

template<typename Real>
void ROL::BoundConstraint< Real >::pruneActive ( Vector< Real > & v,
const Vector< Real > & g,
const Vector< Real > & x,
Real xeps = Real(0),
Real geps = Real(0) )

Set variables to zero if they correspond to the \(\epsilon\)-binding set.

This function sets \(v(\xi)=0\) if \(\xi\in\mathcal{B}_\epsilon(x)\). Here, the \(\epsilon\)-binding set is defined as

\[ \mathcal{B}^+_\epsilon(x) = \mathcal{B}^+_\epsilon(x)\cap\mathcal{B}^-_\epsilon(x). \]

Parameters
[out]vis the variable to be pruned.
[in]gis the negative search direction.
[in]xis the current optimization variable.
[in]xepsis the active-set tolerance \(\epsilon_x\).
[in]gepsis the binding-set tolerance \(\epsilon_g\).

◆ pruneLowerInactive() [1/2]

template<typename Real>
void ROL::BoundConstraint< Real >::pruneLowerInactive ( Vector< Real > & v,
const Vector< Real > & x,
Real eps = Real(0) )

Set variables to zero if they correspond to the \(\epsilon\)-inactive set.

This function sets \(v(\xi)=0\) if \(\xi\in\Xi\setminus\mathcal{A}_\epsilon(x)\). Here,

Parameters
[out]vis the variable to be pruned.
[in]xis the current optimization variable.
[in]epsis the active-set tolerance \(\epsilon\).

Referenced by ROL::TypeB::PrimalDualActiveSetAlgorithm< Real >::run().

◆ pruneUpperInactive() [1/2]

template<typename Real>
void ROL::BoundConstraint< Real >::pruneUpperInactive ( Vector< Real > & v,
const Vector< Real > & x,
Real eps = Real(0) )

Set variables to zero if they correspond to the \(\epsilon\)-inactive set.

This function sets \(v(\xi)=0\) if \(\xi\in\Xi\setminus\mathcal{A}_\epsilon(x)\). Here,

Parameters
[out]vis the variable to be pruned.
[in]xis the current optimization variable.
[in]epsis the active-set tolerance \(\epsilon\).

Referenced by ROL::TypeB::PrimalDualActiveSetAlgorithm< Real >::run().

◆ pruneLowerInactive() [2/2]

template<typename Real>
void ROL::BoundConstraint< Real >::pruneLowerInactive ( Vector< Real > & v,
const Vector< Real > & g,
const Vector< Real > & x,
Real xeps = Real(0),
Real geps = Real(0) )

Set variables to zero if they correspond to the \(\epsilon\)-nonbinding set.

This function sets \(v(\xi)=0\) if \(\xi\in\Xi\setminus\mathcal{B}_\epsilon(x)\).

Parameters
[out]vis the variable to be pruned.
[in]xis the current optimization variable.
[in]gis the negative search direction.
[in]xepsis the active-set tolerance \(\epsilon_x\).
[in]gepsis the binding-set tolerance \(\epsilon_g\).

◆ pruneUpperInactive() [2/2]

template<typename Real>
void ROL::BoundConstraint< Real >::pruneUpperInactive ( Vector< Real > & v,
const Vector< Real > & g,
const Vector< Real > & x,
Real xeps = Real(0),
Real geps = Real(0) )

Set variables to zero if they correspond to the \(\epsilon\)-nonbinding set.

This function sets \(v(\xi)=0\) if \(\xi\in\Xi\setminus\mathcal{B}_\epsilon(x)\).

Parameters
[out]vis the variable to be pruned.
[in]xis the current optimization variable.
[in]gis the negative search direction.
[in]xepsis the active-set tolerance \(\epsilon_x\).
[in]gepsis the binding-set tolerance \(\epsilon_g\).

◆ pruneInactive() [1/2]

template<typename Real>
void ROL::BoundConstraint< Real >::pruneInactive ( Vector< Real > & v,
const Vector< Real > & x,
Real eps = Real(0) )

Set variables to zero if they correspond to the \(\epsilon\)-inactive set.

This function sets \(v(\xi)=0\) if \(\xi\in\Xi\setminus\mathcal{A}_\epsilon(x)\). Here,

Parameters
[out]vis the variable to be pruned.
[in]xis the current optimization variable.
[in]epsis the active-set tolerance \(\epsilon\).

Referenced by ROL::TypeB::KelleySachsAlgorithm< Real >::applyFreeHessian(), ROL::TypeB::KelleySachsAlgorithm< Real >::applyFreePrecond(), ROL::ProjectedNewtonStep< Real >::compute(), ROL::ProjectedSecantStep< Real >::compute(), ROL::LineSearchStep< Real >::GradDotStep(), ROL::TypeB::PrimalDualActiveSetAlgorithm< Real >::run(), and ROL::LineSearch< Real >::status().

◆ pruneInactive() [2/2]

template<typename Real>
void ROL::BoundConstraint< Real >::pruneInactive ( Vector< Real > & v,
const Vector< Real > & g,
const Vector< Real > & x,
Real xeps = Real(0),
Real geps = Real(0) )

Set variables to zero if they correspond to the \(\epsilon\)-nonbinding set.

This function sets \(v(\xi)=0\) if \(\xi\in\Xi\setminus\mathcal{B}_\epsilon(x)\).

Parameters
[out]vis the variable to be pruned.
[in]xis the current optimization variable.
[in]gis the negative search direction.
[in]xepsis the active-set tolerance \(\epsilon_x\).
[in]gepsis the binding-set tolerance \(\epsilon_g\).

◆ computeProjectedGradient()

template<typename Real>
void ROL::BoundConstraint< Real >::computeProjectedGradient ( Vector< Real > & g,
const Vector< Real > & x )

Compute projected gradient.

This function projects the gradient \(g\) onto the tangent cone.

Parameters
[in,out]gis the gradient of the objective function at x.
[in]xis the optimization variable

Referenced by ROL::TrustRegionStep< Real >::computeCriticalityMeasure(), ROL::ProjectedNewtonKrylovStep< Real >::update(), ROL::ProjectedNewtonStep< Real >::update(), and ROL::ProjectedSecantStep< Real >::update().

◆ computeProjectedStep()

template<typename Real>
void ROL::BoundConstraint< Real >::computeProjectedStep ( Vector< Real > & v,
const Vector< Real > & x )

Compute projected step.

This function computes the projected step \(P_{[a,b]}(x+v) - x\).

Parameters
[in,out]vis the step variable.
[in]xis the optimization variable.

Member Data Documentation

◆ Lactivated_

template<typename Real>
bool ROL::BoundConstraint< Real >::Lactivated_
private

Flag that determines whether or not the lower bounds are being used.

Definition at line 75 of file ROL_BoundConstraint.hpp.

◆ Uactivated_

template<typename Real>
bool ROL::BoundConstraint< Real >::Uactivated_
private

Flag that determines whether or not the upper bounds are being used.

Definition at line 76 of file ROL_BoundConstraint.hpp.

◆ lower_

template<typename Real>
Ptr<Vector<Real> > ROL::BoundConstraint< Real >::lower_
protected

Definition at line 79 of file ROL_BoundConstraint.hpp.

◆ upper_

template<typename Real>
Ptr<Vector<Real> > ROL::BoundConstraint< Real >::upper_
protected

Definition at line 80 of file ROL_BoundConstraint.hpp.


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