libtrilinos-rol-dev 12.12.1-5 / usr / include / trilinos / ROL_InteriorPoint.hpp

//               Rapid Optimization Library (ROL) Package
//                 Copyright (2014) Sandia Corporation
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#ifndef ROL_INTERIORPOINT_H
#define ROL_INTERIORPOINT_H

#include "ROL_PartitionedVector.hpp"
#include "ROL_Objective.hpp"
#include "ROL_InequalityConstraint.hpp"

namespace ROL {

namespace InteriorPoint {

/** @ingroup func_group
 *  \class ROL::PenalizedObjective
 *  \brief Adds barrier term to generic objective
 */
template <class Real>
class PenalizedObjective : public ROL::Objective<Real> {
private:

  typedef Vector<Real>            V;
  typedef PartitionedVector<Real> PV;
  typedef typename PV::size_type  size_type;

  const static size_type OPT   = 0;
  const static size_type SLACK = 1;

  Teuchos::RCP<Objective<Real> > obj_;
  Teuchos::RCP<Objective<Real> > slack_barrier_;
  Teuchos::RCP<Objective<Real> > bc_barrier_;
  Teuchos::RCP<PV>    x_;
  Teuchos::RCP<PV>    g_;
  Teuchos::RCP<V>     scratch_;


  Real mu_;
  int nfval_;
  int ngval_;
  Real fval_;
  Real gnorm_;
  bool hasBoundConstraint_;

public:

  // Constructor without BoundConstraint
  PenalizedObjective( const Teuchos::RCP<Objective<Real> > &obj,
                      const Teuchos::RCP<Objective<Real> > &slack_barrier,
                      const Vector<Real> &x,
                      Real mu ) :
    obj_(obj), slack_barrier_(slack_barrier), bc_barrier_(Teuchos::null),
    x_(Teuchos::null), g_(Teuchos::null), scratch_(Teuchos::null),
    mu_(mu), nfval_(0), ngval_(0), fval_(0.0), gnorm_(0.0),
    hasBoundConstraint_(false)  {

    const PV &xpv = Teuchos::dyn_cast<const PV>(x);

    x_ = Teuchos::rcp_static_cast<PV>(xpv.clone());
    g_ = Teuchos::rcp_static_cast<PV>(xpv.dual().clone());
  }


  // Constructor with BoundConstraint
  PenalizedObjective( const Teuchos::RCP<Objective<Real> > &obj,
                      const Teuchos::RCP<Objective<Real> > &slack_barrier,
                      const Teuchos::RCP<Objective<Real> > &bc_barrier,
                      const Vector<Real> &x,
                      Real mu ) :
    obj_(obj), slack_barrier_(slack_barrier), bc_barrier_(bc_barrier),
    x_(Teuchos::null), g_(Teuchos::null), scratch_(Teuchos::null),
    mu_(mu), nfval_(0), ngval_(0), fval_(0.0), gnorm_(0.0),
    hasBoundConstraint_(true)  {

    const PV &xpv = Teuchos::dyn_cast<const PV>(x);

    x_ = Teuchos::rcp_static_cast<PV>(xpv.clone());
    g_ = Teuchos::rcp_static_cast<PV>(xpv.dual().clone());

    scratch_ = g_->get(OPT)->clone();
  }




  void updatePenalty( Real mu ) {
    mu_ = mu;
  }

  int getNumberFunctionEvaluations(void) {
    return nfval_;
  }

  int getNumberGradientEvaluations(void) {
    return ngval_;
  }

  void reset(void) {
    nfval_ = 0.; nfval_ = 0.;
  }

  /** \brief Update barrier penalized objective function

      This function updates the penalized objective 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 ) {

    const PV &xpv = Teuchos::dyn_cast<const PV>(x);

    Teuchos::RCP<const V> xo = xpv.get(OPT);
    Teuchos::RCP<const V> xs = xpv.get(SLACK);

    obj_->update(*xo,flag,iter);
    slack_barrier_->update(*xs,flag,iter);

    if(hasBoundConstraint_) {
      bc_barrier_->update(*xo,flag,iter);
    }

  }

  /** \brief Compute value.

      This function returns the barrier objective value.
      @param[in]          x   is the current iterate.
      @param[in]          tol is a tolerance.
  */
  Real value( const Vector<Real> &x, Real &tol ) {

    const PV &xpv = Teuchos::dyn_cast<const PV>(x);

    Teuchos::RCP<const V> xo = xpv.get(OPT);
    Teuchos::RCP<const V> xs = xpv.get(SLACK);

    Real val = 0;

    // Compute objective function value
    fval_ = obj_->value(*xo,tol);
    Real pval = slack_barrier_->value(*xs,tol);

    val = fval_ + mu_*pval;

    if( hasBoundConstraint_ ) {
      Real bval = bc_barrier_->value(*xo,tol);
      val += mu_*bval;
    }

    ++nfval_;

    return val;
  }

  Real getObjectiveValue() {
    return fval_;
  }


  /** \brief Compute gradient.

      This function returns the barrier penalized objective gradient.
      @param[out]         g   is the gradient.
      @param[in]          x   is the current iterate.
      @param[in]          tol is a tolerance.
  */
  void gradient( Vector<Real> &g, const Vector<Real> &x, Real &tol ) {

      // Compute objective function gradient
      const PV &xpv = Teuchos::dyn_cast<const PV>(x);
      PV &gpv = Teuchos::dyn_cast<PV>(g);

      Teuchos::RCP<const V> xo = xpv.get(OPT);
      Teuchos::RCP<const V> xs = xpv.get(SLACK);

      Teuchos::RCP<V> go = gpv.get(OPT);
      Teuchos::RCP<V> gs = gpv.get(SLACK);

      obj_->gradient(*go,*xo,tol);

      if( hasBoundConstraint_ ) {
        bc_barrier_->gradient(*scratch_,*xo,tol);
        scratch_->scale(mu_);
        go->plus(*scratch_);
      }

      slack_barrier_->gradient(*gs,*xs,tol);
      gs->scale(mu_);

      g_->set(g);
      g_->zero(SLACK);

      gnorm_ = g.norm();

      ++ngval_;

  }

  void getObjectiveGradient( Vector<Real> &g ) {

  }

  Real getGradientNorm() {
    return gnorm_;
  }

  /** \brief Apply Hessian approximation to vector.

      This function applies the Hessian of the barrier penalized objective
      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.
  */
  void hessVec( Vector<Real> &hv, const Vector<Real> &v,
                 const Vector<Real> &x, Real &tol ) {

    using Teuchos::RCP;  using Teuchos::dyn_cast;

    const PV &xpv = dyn_cast<const PV>(x);
    const PV &vpv = dyn_cast<const PV>(v);
    PV &hvpv = dyn_cast<PV>(hv);

    RCP<const V> xo = xpv.get(OPT);
    RCP<const V> xs = xpv.get(SLACK);

    RCP<const V> vo = vpv.get(OPT);
    RCP<const V> vs = vpv.get(SLACK);

    RCP<V> hvo = hvpv.get(OPT);
    RCP<V> hvs = hvpv.get(SLACK);

    obj_->hessVec(*hvo, *vo, *xo, tol);

    if( hasBoundConstraint_ ) {
      bc_barrier_->hessVec(*scratch_,*vo,*xo,tol);
      scratch_->scale(mu_);
      hvo->plus(*scratch_);

    }

    slack_barrier_->hessVec(*hvs, *vs, *xs, tol);
    hvs->scale(mu_);

  }

}; // class InteriorPointObjective



/** @ingroup func_group
 *  \class ROL::InteriorPoint::CompositeConstraint
 *  \brief Has both inequality and equality constraints.
 *        Treat inequality constraint as equality with slack variable
 */

template<class Real>
class CompositeConstraint : public EqualityConstraint<Real> {
private:

  typedef Vector<Real>            V;
  typedef PartitionedVector<Real> PV;
  typedef typename PV::size_type  size_type;

  const static size_type OPT   = 0;
  const static size_type SLACK = 1;

  const static size_type INEQ  = 0;
  const static size_type EQUAL = 1;

  Teuchos::RCP<InequalityConstraint<Real> > incon_;
  Teuchos::RCP<EqualityConstraint<Real> >   eqcon_;

  bool hasEquality_;         // True if an equality constraint is present
  int  ncval_;               // Number of constraint evaluations


public:

  // Constructor with inequality and equality constraints
  CompositeConstraint( const Teuchos::RCP<InequalityConstraint<Real> > &incon,
                       const Teuchos::RCP<EqualityConstraint<Real> > &eqcon ) :
                       incon_(incon), eqcon_(eqcon),
                       hasEquality_(true), ncval_(0) { }

  // Constructor with inequality constraint only
  CompositeConstraint( const Teuchos::RCP<InequalityConstraint<Real> > &incon ) :
                       incon_(incon), eqcon_(Teuchos::null),
                       hasEquality_(false), ncval_(0) { }


  int getNumberConstraintEvaluations(void) {
    return ncval_;
  }

  void update( const Vector<Real> &x, bool flag = true, int iter = -1 ) {

    const PV &xpv = Teuchos::dyn_cast<const PV>(x);

    Teuchos::RCP<const V> xo = xpv.get(OPT);
    Teuchos::RCP<const V> xs = xpv.get(SLACK);

    incon_->update(*xo,flag,iter);

    if( hasEquality_ ) {
      eqcon_->update(*xo,flag,iter);
    }

  }

  void value( Vector<Real> &c, const Vector<Real> &x, Real &tol ) {

    PV &cpv = Teuchos::dyn_cast<PV>(c);
    const PV &xpv = Teuchos::dyn_cast<const PV>(x);

    Teuchos::RCP<const V> xo = xpv.get(OPT);
    Teuchos::RCP<const V> xs = xpv.get(SLACK);

    Teuchos::RCP<V> ci = cpv.get(INEQ);
    Teuchos::RCP<V> ce;

    incon_->value(*ci, *xo, tol);
    ci->axpy(-1.0,*xs);

    if(hasEquality_) {
      ce = cpv.get(EQUAL);
      eqcon_->value(*ce, *xo, tol);
    }

    ++ncval_;

  }

  void applyJacobian( Vector<Real> &jv,
                      const Vector<Real> &v,
                      const Vector<Real> &x,
                      Real &tol ) {

    using Teuchos::RCP;  using Teuchos::dyn_cast;

    // Partition vectors and extract subvectors
    const PV &xpv = dyn_cast<const PV>(x);
    const PV &vpv = dyn_cast<const PV>(v);

    RCP<const V> xo = xpv.get(OPT);
    RCP<const V> xs = xpv.get(SLACK);

    RCP<const V> vo = vpv.get(OPT);
    RCP<const V> vs = vpv.get(SLACK);

    PV &jvpv = dyn_cast<PV>(jv);

    RCP<V> jvi = jvpv.get(INEQ);
    incon_->applyJacobian(*jvi, *vo, *xo, tol);
    jvi->axpy(-1.0,*vs);

    if(hasEquality_) {
      RCP<V> jve = jvpv.get(EQUAL);
      eqcon_->applyJacobian(*jve, *vo, *xo, tol);
    }

  }

  void applyAdjointJacobian( Vector<Real> &ajv,
                             const Vector<Real> &v,
                             const Vector<Real> &x,
                             Real &tol ) {

    using Teuchos::RCP;  using Teuchos::dyn_cast;

    // Partition vectors and extract subvectors
    const PV &xpv = dyn_cast<const PV>(x);
    PV &ajvpv = dyn_cast<PV>(ajv);

    RCP<const V> xo = xpv.get(OPT);
    RCP<const V> xs = xpv.get(SLACK);

    RCP<V> ajvo = ajvpv.get(OPT);
    RCP<V> ajvs = ajvpv.get(SLACK);

    const PV &vpv = dyn_cast<const PV>(v);

    RCP<const V> vi = vpv.get(INEQ);

    incon_->applyAdjointJacobian(*ajvo,*vi,*xo,tol);

    ajvs->set(*vi);
    ajvs->scale(-1.0);

    if(hasEquality_) {

      RCP<const V> ve = vpv.get(EQUAL);
      RCP<V> temp = ajvo->clone();
      eqcon_->applyAdjointJacobian(*temp,*ve,*xo,tol);
      ajvo->plus(*temp);

    }

  }

  void applyAdjointHessian( Vector<Real> &ahuv,
                            const Vector<Real> &u,
                            const Vector<Real> &v,
                            const Vector<Real> &x,
                            Real &tol ) {

    using Teuchos::RCP;  using Teuchos::dyn_cast;

    const PV &xpv = dyn_cast<const PV>(x);
    const PV &vpv = dyn_cast<const PV>(v);
    PV &ahuvpv = dyn_cast<PV>(ahuv);

    RCP<const V> xo = xpv.get(OPT);
    RCP<const V> xs = xpv.get(SLACK);

    RCP<const V> vo = vpv.get(OPT);

    RCP<V> ahuvo = ahuvpv.get(OPT);
    RCP<V> ahuvs = ahuvpv.get(SLACK);

    RCP<V> temp = ahuvo->clone();

    const PV &upv = dyn_cast<const PV>(u);

    RCP<const V> ui = upv.get(INEQ);

    incon_->applyAdjointHessian(*ahuvo,*ui,*vo,*xo,tol);
    ahuvs->zero();

    if(hasEquality_) {
      RCP<const V> ue   = upv.get(EQUAL);
      eqcon_->applyAdjointHessian(*temp,*ue,*vo,*xo,tol);
      ahuvo->plus(*temp);
    }

  }

}; // class CompositeConstraint

} // namespace InteriorPoint
} // namespace ROL

#endif