ROL_TypeB_LinMoreAlgorithm.hpp

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#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_; 
 
  // 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