/usr/include/trilinos/ROL_MoreauYosidaPenalty.hpp is in libtrilinos-rol-dev 12.10.1-3.
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// ************************************************************************
//
// Rapid Optimization Library (ROL) Package
// Copyright (2014) Sandia Corporation
//
// Under terms of Contract DE-AC04-94AL85000, there is a non-exclusive
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// @HEADER
#ifndef ROL_MOREAUYOSIDAPENALTY_H
#define ROL_MOREAUYOSIDAPENALTY_H
#include "ROL_Objective.hpp"
#include "ROL_BoundConstraint.hpp"
#include "ROL_Vector.hpp"
#include "ROL_Types.hpp"
#include "Teuchos_RCP.hpp"
#include <iostream>
/** @ingroup func_group
\class ROL::MoreauYosidaPenalty
\brief Provides the interface to evaluate the Moreau-Yosida penalty function.
---
*/
namespace ROL {
template <class Real>
class MoreauYosidaPenalty : public Objective<Real> {
private:
const Teuchos::RCP<Objective<Real> > obj_;
const Teuchos::RCP<BoundConstraint<Real> > con_;
Teuchos::RCP<Vector<Real> > g_;
Teuchos::RCP<Vector<Real> > l_;
Teuchos::RCP<Vector<Real> > u_;
Teuchos::RCP<Vector<Real> > l1_;
Teuchos::RCP<Vector<Real> > u1_;
Teuchos::RCP<Vector<Real> > dl1_;
Teuchos::RCP<Vector<Real> > du1_;
Teuchos::RCP<Vector<Real> > xlam_;
Teuchos::RCP<Vector<Real> > v_;
Teuchos::RCP<Vector<Real> > dv_;
Teuchos::RCP<Vector<Real> > dv2_;
Teuchos::RCP<Vector<Real> > lam_;
Teuchos::RCP<Vector<Real> > tmp_;
Real mu_;
Real fval_;
bool isConEvaluated_;
int nfval_;
int ngval_;
void computePenalty(const Vector<Real> &x) {
if ( con_->isActivated() ) {
Real one = 1.0;
if ( !isConEvaluated_ ) {
xlam_->set(x);
xlam_->axpy(one/mu_,*lam_);
if ( con_->isFeasible(*xlam_) ) {
l1_->zero(); dl1_->zero();
u1_->zero(); du1_->zero();
}
else {
// Compute lower penalty component
l1_->set(*l_);
con_->pruneLowerInactive(*l1_,*xlam_);
tmp_->set(*xlam_);
con_->pruneLowerInactive(*tmp_,*xlam_);
l1_->axpy(-one,*tmp_);
// Compute upper penalty component
u1_->set(*xlam_);
con_->pruneUpperInactive(*u1_,*xlam_);
tmp_->set(*u_);
con_->pruneUpperInactive(*tmp_,*xlam_);
u1_->axpy(-one,*tmp_);
// Compute derivative of lower penalty component
dl1_->set(l1_->dual());
con_->pruneLowerInactive(*dl1_,*xlam_);
// Compute derivative of upper penalty component
du1_->set(u1_->dual());
con_->pruneUpperInactive(*du1_,*xlam_);
}
isConEvaluated_ = true;
}
}
}
public:
~MoreauYosidaPenalty() {}
MoreauYosidaPenalty(const Teuchos::RCP<Objective<Real> > &obj,
const Teuchos::RCP<BoundConstraint<Real> > &con,
const ROL::Vector<Real> &x, const Real mu = 1.0)
: obj_(obj), con_(con), mu_(mu),
fval_(0), isConEvaluated_(false), nfval_(0), ngval_(0) {
g_ = x.dual().clone();
l_ = x.clone();
l1_ = x.clone();
dl1_ = x.dual().clone();
u_ = x.clone();
u1_ = x.clone();
du1_ = x.dual().clone();
xlam_ = x.clone();
v_ = x.clone();
dv_ = x.dual().clone();
dv2_ = x.dual().clone();
lam_ = x.clone();
tmp_ = x.clone();
con_->setVectorToLowerBound(*l_);
con_->setVectorToUpperBound(*u_);
lam_->zero();
//lam_->set(*u_);
//lam_->plus(*l_);
//lam_->scale(0.5);
}
void updateMultipliers(Real mu, const ROL::Vector<Real> &x) {
if ( con_->isActivated() ) {
Real one = 1.0;
computePenalty(x);
lam_->set(*u1_);
lam_->axpy(-one,*l1_);
lam_->scale(mu_);
mu_ = mu;
}
nfval_ = 0; ngval_ = 0;
isConEvaluated_ = false;
}
Real getObjectiveValue(void) const {
return fval_;
}
Teuchos::RCP<Vector<Real> > getGradient(void) const {
return g_;
}
int getNumberFunctionEvaluations(void) {
return nfval_;
}
int getNumberGradientEvaluations(void) {
return ngval_;
}
/** \brief Update Moreau-Yosida penalty function.
This function updates the Moreau-Yosida penalty function at new iterations.
@param[in] x is the new iterate.
@param[in] flag is true if the iterate has changed.
@param[in] iter is the outer algorithm iterations count.
*/
void update( const Vector<Real> &x, bool flag = true, int iter = -1 ) {
obj_->update(x,flag,iter);
con_->update(x,flag,iter);
isConEvaluated_ = false;
}
/** \brief Compute value.
This function returns the Moreau-Yosida penalty value.
@param[in] x is the current iterate.
@param[in] tol is a tolerance for inexact Moreau-Yosida penalty computation.
*/
Real value( const Vector<Real> &x, Real &tol ) {
Real half = 0.5;
// Compute objective function value
fval_ = obj_->value(x,tol);
nfval_++;
// Add value of the Moreau-Yosida penalty
Real fval = fval_;
if ( con_->isActivated() ) {
computePenalty(x);
fval += half*mu_*(l1_->dot(*l1_) + u1_->dot(*u1_));
}
return fval;
}
/** \brief Compute gradient.
This function returns the Moreau-Yosida penalty gradient.
@param[out] g is the gradient.
@param[in] x is the current iterate.
@param[in] tol is a tolerance for inexact Moreau-Yosida penalty computation.
*/
void gradient( Vector<Real> &g, const Vector<Real> &x, Real &tol ) {
// Compute gradient of objective function
obj_->gradient(*g_,x,tol);
ngval_++;
g.set(*g_);
// Add gradient of the Moreau-Yosida penalty
if ( con_->isActivated() ) {
computePenalty(x);
g.axpy(-mu_,*dl1_);
g.axpy(mu_,*du1_);
}
}
/** \brief Apply Hessian approximation to vector.
This function applies the Hessian of the Moreau-Yosida penalty to the vector \f$v\f$.
@param[out] hv is the the action of the Hessian on \f$v\f$.
@param[in] v is the direction vector.
@param[in] x is the current iterate.
@param[in] tol is a tolerance for inexact Moreau-Yosida penalty computation.
*/
void hessVec( Vector<Real> &hv, const Vector<Real> &v, const Vector<Real> &x, Real &tol ) {
// Apply objective Hessian to a vector
obj_->hessVec(hv,v,x,tol);
// Add Hessian of the Moreau-Yosida penalty
if ( con_->isActivated() ) {
Real one = 1.0;
computePenalty(x);
v_->set(v);
con_->pruneLowerActive(*v_,*xlam_);
v_->scale(-one);
v_->plus(v);
dv_->set(v_->dual());
dv2_->set(*dv_);
con_->pruneLowerActive(*dv_,*xlam_);
dv_->scale(-one);
dv_->plus(*dv2_);
hv.axpy(mu_,*dv_);
v_->set(v);
con_->pruneUpperActive(*v_,*xlam_);
v_->scale(-one);
v_->plus(v);
dv_->set(v_->dual());
dv2_->set(*dv_);
con_->pruneUpperActive(*dv_,*xlam_);
dv_->scale(-one);
dv_->plus(*dv2_);
hv.axpy(mu_,*dv_);
}
}
// Definitions for parametrized (stochastic) objective functions
public:
void setParameter(const std::vector<Real> ¶m) {
Objective<Real>::setParameter(param);
obj_->setParameter(param);
}
}; // class MoreauYosidaPenalty
} // namespace ROL
#endif
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