ROL_TypeB_LinMoreAlgorithm.hpp

Go to the documentation of this file.

// @HEADER
// ************************************************************************
//
//               Rapid Optimization Library (ROL) Package
//                 Copyright (2014) Sandia Corporation
//
// Under terms of Contract DE-AC04-94AL85000, there is a non-exclusive
// license for use of this work by or on behalf of the U.S. Government.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are
// met:
//
// 1. Redistributions of source code must retain the above copyright
// notice, this list of conditions and the following disclaimer.
//
// 2. Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in the
// documentation and/or other materials provided with the distribution.
//
// 3. Neither the name of the Corporation nor the names of the
// contributors may be used to endorse or promote products derived from
// this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY SANDIA CORPORATION "AS IS" AND ANY
// EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL SANDIA CORPORATION OR THE
// CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
// EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
// PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
// NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
//
// Questions? Contact lead developers:
//              Drew Kouri   (dpkouri@sandia.gov) and
//              Denis Ridzal (dridzal@sandia.gov)
//
// ************************************************************************
// @HEADER

#ifndef ROL_TYPEB_LINMOREALGORITHM_HPP
#define ROL_TYPEB_LINMOREALGORITHM_HPP

#include "ROL_TypeB_Algorithm.hpp"
#include "ROL_TrustRegionModel_U.hpp"
#include "ROL_TrustRegionUtilities.hpp"
#include "ROL_NullSpaceOperator.hpp"
#include "ROL_ReducedLinearConstraint.hpp"

namespace ROL {
namespace TypeB {

template<typename Real>
class LinMoreAlgorithm : public TypeB::Algorithm<Real> {
private:
  Ptr<TrustRegionModel_U<Real>> model_;  

  // TRUST REGION PARAMETERS
  Real delMax_; 
  Real eta0_;   
  Real eta1_;   
  Real eta2_;   
  Real gamma0_; 
  Real gamma1_; 
  Real gamma2_; 
  Real TRsafe_; 
  Real eps_;    
  bool interpRad_; 

  // NONMONOTONE PARAMETER
  bool useNM_;
  int storageNM_;

  // ITERATION FLAGS/INFORMATION
  TRUtils::ETRFlag TRflag_; 
  int SPflag_;              
  int SPiter_;              

  // SECANT INFORMATION
  ESecant esec_;          
  bool useSecantPrecond_; 
  bool useSecantHessVec_; 

  // TRUNCATED CG INFORMATION
  Real tol1_; 
  Real tol2_; 
  int maxit_; 

  // ALGORITHM SPECIFIC PARAMETERS
  int minit_;      
  Real mu0_;       
  Real spexp_;     
  int  redlim_;    
  int  explim_;    
  Real alpha_;     
  bool normAlpha_; 
  Real interpf_;   
  Real extrapf_;   
  Real qtol_;      
  Real interpfPS_; 
  int pslim_;      

  mutable int nhess_;  
  unsigned verbosity_; 
  bool writeHeader_;   

  bool hasEcon_;                            
  Ptr<ReducedLinearConstraint<Real>> rcon_; 
  Ptr<NullSpaceOperator<Real>> ns_;         

  using TypeB::Algorithm<Real>::state_;
  using TypeB::Algorithm<Real>::status_;
  using TypeB::Algorithm<Real>::proj_;

public:
  LinMoreAlgorithm(ParameterList &list, const Ptr<Secant<Real>> &secant = nullPtr);

  using TypeB::Algorithm<Real>::run;
  void run( Vector<Real>          &x,
            const Vector<Real>    &g, 
            Objective<Real>       &obj,
            BoundConstraint<Real> &bnd,
            std::ostream          &outStream = std::cout) override;

  void writeHeader( std::ostream& os ) const override;

  void writeName( std::ostream& os ) const override;

  void writeOutput( std::ostream& os, bool write_header = false ) const override;

private:
  void initialize(Vector<Real>          &x,
                  const Vector<Real>    &g,
                  Objective<Real>       &obj,
                  BoundConstraint<Real> &bnd,
                  std::ostream &outStream = std::cout);

  // Compute the projected step s = P(x + alpha*w) - x
  // Returns the norm of the projected step s
  //    s     -- The projected step upon return
  //    w     -- The direction vector w (unchanged)
  //    x     -- The anchor vector x (unchanged)
  //    alpha -- The step size (unchanged)
  Real dgpstep(Vector<Real> &s, const Vector<Real> &w,
         const Vector<Real> &x, const Real alpha,
         std::ostream &outStream = std::cout) const;

  // Compute Cauchy point, i.e., the minimizer of q(P(x - alpha*g)-x)
  // subject to the trust region constraint ||P(x - alpha*g)-x|| <= del
  //   s     -- The Cauchy step upon return: Primal optimization space vector
  //   alpha -- The step length for the Cauchy point upon return
  //   x     -- The anchor vector x (unchanged): Primal optimization space vector
  //   g     -- The (dual) gradient vector g (unchanged): Primal optimization space vector
  //   del   -- The trust region radius (unchanged)
  //   model -- Trust region model
  //   dwa   -- Dual working array, stores Hessian applied to step
  //   dwa1  -- Dual working array
  Real dcauchy(Vector<Real> &s, Real &alpha, Real &q,
               const Vector<Real> &x, const Vector<Real> &g,
               const Real del, TrustRegionModel_U<Real> &model,
               Vector<Real> &dwa, Vector<Real> &dwa1,
               std::ostream &outStream = std::cout);

  // Perform projected search to determine beta such that
  // q(P(x + beta*s)-x) <= mu0*g'(P(x + beta*s)-x) for mu0 in (0,1)
  //   x     -- The anchor vector x, upon return x = P(x + beta*s): Primal optimization space vector
  //   s     -- The direction vector s, upon return s = P(x + beta*s) - x: Primal optimization space vector
  //   g     -- The free components of the gradient vector g (unchanged): Primal optimization space vector
  //   model -- Contains objective and bound constraint information
  //   pwa   -- Primal working array
  //   dwa   -- Dual working array
  Real dprsrch(Vector<Real> &x, Vector<Real> &s, Real &q,
               const Vector<Real> &g, TrustRegionModel_U<Real> &model,
               BoundConstraint<Real> &bnd,
               Vector<Real> &pwa, Vector<Real> &dwa,
               std::ostream &outStream = std::cout);

  // Compute sigma such that ||x+sigma*p||_inv(M) = del.  This is called
  // if dtrpcg detects negative curvature or if the step violates
  // the trust region bound
  //   xtx -- The dot product <x, inv(M)x> (unchanged)
  //   ptp -- The dot product <p, inv(M)p> (unchanged)
  //   ptx -- The dot product <p, inv(M)x> (unchanged)
  //   del -- Trust region radius (unchanged)
  Real dtrqsol(const Real xtx, const Real ptp, const Real ptx, const Real del) const;

  // Solve the trust region subproblem: minimize q(w) subject to the
  // trust region constraint ||w||_inv(M) <= del using the Steihaug-Toint
  // Conjugate Gradients algorithm
  //   w       -- The step vector to be computed
  //   iflag   -- Termination flag
  //   iter    -- Number of CG iterations
  //   del     -- Trust region radius (unchanged)
  //   model   -- Trust region model
  //   bnd     -- Bound constraint used to remove active variables
  //   tol     -- Residual stopping tolerance (unchanged)
  //   stol    -- Preconditioned residual stopping tolerance (unchanged)
  //   itermax -- Maximum number of iterations
  //   p       -- Primal working array that stores the CG step
  //   q       -- Dual working array that stores the Hessian applied to p
  //   r       -- Primal working array that stores the preconditioned residual
  //   t       -- Dual working array that stores the residual
  //   pwa     -- Primal working array that stores the pruned vector in hessVec
  //   dwa     -- Dual working array that stores the pruned vector in precond
  Real dtrpcg(Vector<Real> &w, int &iflag, int &iter,
              const Vector<Real> &g, const Vector<Real> &x,
              const Real del, TrustRegionModel_U<Real> &model, BoundConstraint<Real> &bnd,
              const Real tol, const Real stol, const int itermax,
              Vector<Real> &p, Vector<Real> &q, Vector<Real> &r,
              Vector<Real> &t, Vector<Real> &pwa, Vector<Real> &dwa,
              std::ostream &outStream = std::cout) const;

  void applyFreeHessian(Vector<Real> &hv,
                       const Vector<Real> &v,
                       const Vector<Real> &x,
                       TrustRegionModel_U<Real> &model,
                       BoundConstraint<Real> &bnd,
                       Real &tol,
                       Vector<Real> &pwa) const;

  void applyFreePrecond(Vector<Real> &hv,
                        const Vector<Real> &v,
                        const Vector<Real> &x,
                        TrustRegionModel_U<Real> &model,
                        BoundConstraint<Real> &bnd,
                        Real &tol,
                        Vector<Real> &dwa,
                        Vector<Real> &pwa) const;

}; // class ROL::TypeB::LinMoreAlgorithm

} // namespace TypeB
} // namespace ROL

#include "ROL_TypeB_LinMoreAlgorithm_Def.hpp"

#endif