ROL_Reduced_AugmentedLagrangian_SimOpt.hpp

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// @HEADER
// *****************************************************************************
//               Rapid Optimization Library (ROL) Package
//
// Copyright 2014 NTESS and the ROL contributors.
// SPDX-License-Identifier: BSD-3-Clause
// *****************************************************************************
// @HEADER
 
#ifndef ROL_REDUCED_AUGMENTEDLAGRANGIAN_SIMOPT_H
#define ROL_REDUCED_AUGMENTEDLAGRANGIAN_SIMOPT_H
 
#include "ROL_Objective_SimOpt.hpp"
#include "ROL_Reduced_Objective_SimOpt.hpp"
#include "ROL_Constraint_SimOpt.hpp"
#include "ROL_AugmentedLagrangian_SimOpt.hpp"
#include "ROL_AugmentedLagrangian.hpp"
#include "ROL_Vector.hpp"
#include "ROL_Types.hpp"
#include "ROL_Ptr.hpp"
#include <iostream>
 
namespace ROL {
 
template <class Real>
class Reduced_AugmentedLagrangian_SimOpt : public AugmentedLagrangian<Real> {
private:
  ROL::Ptr<AugmentedLagrangian_SimOpt<Real> > augLagSimOpt_;
  ROL::Ptr<Reduced_Objective_SimOpt<Real> > rAugLagSimOpt_;
  ROL::Ptr<Vector<Real> > state_;
 
  // Evaluation counters
  int ngval_;
 
public:
  Reduced_AugmentedLagrangian_SimOpt(const ROL::Ptr<Objective_SimOpt<Real> > &obj,
                                     const ROL::Ptr<Constraint_SimOpt<Real> > &redCon,
                                     const ROL::Ptr<Constraint_SimOpt<Real> > &augCon,
                                     const ROL::Ptr<Vector<Real> > &state,
                                     const ROL::Ptr<Vector<Real> > &control,
                                     const ROL::Ptr<Vector<Real> > &adjoint,
                                     const ROL::Ptr<Vector<Real> > &augConVec,
                                     const ROL::Ptr<Vector<Real> > &multiplier,
                                     const Real penaltyParameter,
                                     ROL::ParameterList &parlist) : state_(state),
                                     ngval_(0) {
 
    augLagSimOpt_ = ROL::makePtr<AugmentedLagrangian_SimOpt<Real>>(obj,
                                                                      augCon,
                                                                      *multiplier,
                                                                      penaltyParameter,
                                                                      *state,
                                                                      *control,
                                                                      *augConVec,
                                                                      parlist);
    rAugLagSimOpt_ = ROL::makePtr<Reduced_Objective_SimOpt<Real>>(augLagSimOpt_,redCon,state,control,adjoint);
    rAugLagSimOpt_->update(*control);
    Real tol = 1e-8;
    rAugLagSimOpt_->value(*control,tol);
  }
 
  void update( const Vector<Real> &x, bool flag = true, int iter = -1 ) {
    rAugLagSimOpt_->update(x,flag,iter);
  }
 
  Real value( const Vector<Real> &x, Real &tol ) {
    return rAugLagSimOpt_->value(x,tol);
  }
 
  void gradient( Vector<Real> &g, const Vector<Real> &x, Real &tol ) {
    ngval_++;
    rAugLagSimOpt_->gradient(g,x,tol);
  }
 
  void hessVec( Vector<Real> &hv, const Vector<Real> &v, const Vector<Real> &x, Real &tol ) {
    rAugLagSimOpt_->hessVec(hv,v,x,tol);
  }
 
  // Return objective function value
  Real getObjectiveValue(const Vector<Real> &x) {
    return augLagSimOpt_->getObjectiveValue(*state_,x);
  }
 
  // Return constraint value
  void getConstraintVec(Vector<Real> &c, const Vector<Real> &x) {
    augLagSimOpt_->getConstraintVec(c,*state_,x);
  }
 
  // Return total number of constraint evaluations
  int getNumberConstraintEvaluations(void) const {
    return augLagSimOpt_->getNumberConstraintEvaluations();
  }
 
  // Return total number of objective evaluations
  int getNumberFunctionEvaluations(void) const {
    return augLagSimOpt_->getNumberFunctionEvaluations();
  }
 
  // Return total number of gradient evaluations
  int getNumberGradientEvaluations(void) const {
    return ngval_;
    //return augLagSimOpt_->getNumberGradientEvaluations();
  }
 
  // Reset with upated penalty parameter
  void reset(const Vector<Real> &multiplier, const Real penaltyParameter) {
    ngval_ = 0;
    augLagSimOpt_->reset(multiplier,penaltyParameter);
  }
 
// For parametrized (stochastic) objective functions and constraints
public:
  void setParameter(const std::vector<Real> &param) {
    AugmentedLagrangian<Real>::setParameter(param);
    rAugLagSimOpt_->setParameter(param);
  }
}; // class AugmentedLagrangian
 
} // namespace ROL
 
#endif