xref: /dports/math/gravity/Gravity-da941e9/thirdparty/Ipopt/include/coin-or/IpIpoptCalculatedQuantities.hpp

// Copyright (C) 2004, 2011 International Business Machines and others.
// All Rights Reserved.
// This code is published under the Eclipse Public License.
//
// Authors:  Carl Laird, Andreas Waechter     IBM    2004-08-13

#ifndef __IPIPOPTCALCULATEDQUANTITIES_HPP__
#define __IPIPOPTCALCULATEDQUANTITIES_HPP__

#include "IpSmartPtr.hpp"
#include "IpCachedResults.hpp"

#include <string>

namespace Ipopt
{
class IpoptNLP;
class IpoptData;
class Vector;
class Matrix;
class SymMatrix;
class Journalist;
class OptionsList;
class RegisteredOptions;

/** Norm types */
enum ENormType
{
   NORM_1 = 0,
   NORM_2,
   NORM_MAX
};

/** Base class for additional calculated quantities that is special
 *  to a particular type of algorithm, such as the CG penalty
 *  function, or using iterative linear solvers.
 *
 *  The regular IpoptCalculatedQuantities object should be given
 *  a derivation of this base class when it is created.
 */
class IPOPTLIB_EXPORT IpoptAdditionalCq: public ReferencedObject
{
public:
   /**@name Constructors/Destructors */
   //@{
   /** Default Constructor */
   IpoptAdditionalCq()
   { }

   /** Destructor */
   virtual ~IpoptAdditionalCq()
   { }
   //@}

   /** This method is called to initialize the global algorithmic
    *  parameters.
    *
    *  The parameters are taken from the OptionsList object.
    */
   virtual bool Initialize(
      const Journalist&  jnlst,
      const OptionsList& options,
      const std::string& prefix
   ) = 0;

private:
   /**@name Default Compiler Generated Methods
    * (Hidden to avoid implicit creation/calling).
    *
    * These methods are not implemented and
    * we do not want the compiler to implement
    * them for us, so we declare them private
    * and do not define them. This ensures that
    * they will not be implicitly created/called.
    */
   //@{
   /** Copy Constructor */
   IpoptAdditionalCq(
      const IpoptAdditionalCq&);

   /** Default Assignment Operator */
   void operator=(
      const IpoptAdditionalCq&);
   //@}
};

/** Class for all IPOPT specific calculated quantities. */
class IPOPTLIB_EXPORT IpoptCalculatedQuantities: public ReferencedObject
{
public:

   /**@name Constructors/Destructors */
   //@{
   /** Constructor */
   IpoptCalculatedQuantities(
      const SmartPtr<IpoptNLP>&  ip_nlp,
      const SmartPtr<IpoptData>& ip_data
   );
   /** Destructor */
   virtual ~IpoptCalculatedQuantities();
   //@}

   /** Method for setting pointer for additional calculated
    *  quantities.
    *
    *  This needs to be called before Initialized.
    */
   void SetAddCq(
      SmartPtr<IpoptAdditionalCq> add_cq
   )
   {
      DBG_ASSERT(!HaveAddCq());
      add_cq_ = add_cq;
   }

   /** Method detecting if additional object for calculated
    *  quantities has already been set
    */
   bool HaveAddCq()
   {
      return IsValid(add_cq_);
   }

   /** This method must be called to initialize the global
    *  algorithmic parameters.
    *
    *  The parameters are taken from the OptionsList object.
    */
   bool Initialize(
      const Journalist&  jnlst,
      const OptionsList& options,
      const std::string& prefix
   );

   /** @name Slacks */
   //@{
   /** Slacks for x_L (at current iterate) */
   SmartPtr<const Vector> curr_slack_x_L();
   /** Slacks for x_U (at current iterate) */
   SmartPtr<const Vector> curr_slack_x_U();
   /** Slacks for s_L (at current iterate) */
   SmartPtr<const Vector> curr_slack_s_L();
   /** Slacks for s_U (at current iterate) */
   SmartPtr<const Vector> curr_slack_s_U();
   /** Slacks for x_L (at trial point) */
   SmartPtr<const Vector> trial_slack_x_L();
   /** Slacks for x_U (at trial point) */
   SmartPtr<const Vector> trial_slack_x_U();
   /** Slacks for s_L (at trial point) */
   SmartPtr<const Vector> trial_slack_s_L();
   /** Slacks for s_U (at trial point) */
   SmartPtr<const Vector> trial_slack_s_U();
   /** Indicating whether or not we "fudged" the slacks */
   Index AdjustedTrialSlacks();
   /** Reset the flags for "fudged" slacks */
   void ResetAdjustedTrialSlacks();
   //@}

   /** @name Objective function */
   //@{
   /** Value of objective function (at current point) */
   virtual Number curr_f();
   /** Unscaled value of the objective function (at the current point) */
   virtual Number unscaled_curr_f();
   /** Value of objective function (at trial point) */
   virtual Number trial_f();
   /** Unscaled value of the objective function (at the trial point) */
   virtual Number unscaled_trial_f();
   /** Gradient of objective function (at current point) */
   SmartPtr<const Vector> curr_grad_f();
   /** Gradient of objective function (at trial point) */
   SmartPtr<const Vector> trial_grad_f();
   //@}

   /** @name Barrier Objective Function */
   //@{
   /** Barrier Objective Function Value
    * (at current iterate with current mu)
    */
   virtual Number curr_barrier_obj();
   /** Barrier Objective Function Value
    * (at trial point with current mu)
    */
   virtual Number trial_barrier_obj();

   /** Gradient of barrier objective function with respect to x
    * (at current point with current mu)
    */
   SmartPtr<const Vector> curr_grad_barrier_obj_x();
   /** Gradient of barrier objective function with respect to s
    * (at current point with current mu)
    */
   SmartPtr<const Vector> curr_grad_barrier_obj_s();

   /** Gradient of the damping term with respect to x (times kappa_d) */
   SmartPtr<const Vector> grad_kappa_times_damping_x();
   /** Gradient of the damping term with respect to s (times kappa_d) */
   SmartPtr<const Vector> grad_kappa_times_damping_s();
   //@}

   /** @name Constraints */
   //@{
   /** c(x) (at current point) */
   SmartPtr<const Vector> curr_c();
   /** unscaled c(x) (at current point) */
   SmartPtr<const Vector> unscaled_curr_c();
   /** c(x) (at trial point) */
   SmartPtr<const Vector> trial_c();
   /** unscaled c(x) (at trial point) */
   SmartPtr<const Vector> unscaled_trial_c();
   /** d(x) (at current point) */
   SmartPtr<const Vector> curr_d();
   /** unscaled d(x) (at current point) */
   SmartPtr<const Vector> unscaled_curr_d();
   /** d(x) (at trial point) */
   SmartPtr<const Vector> trial_d();
   /** d(x) - s (at current point) */
   SmartPtr<const Vector> curr_d_minus_s();
   /** d(x) - s (at trial point) */
   SmartPtr<const Vector> trial_d_minus_s();
   /** Jacobian of c (at current point) */
   SmartPtr<const Matrix> curr_jac_c();
   /** Jacobian of c (at trial point) */
   SmartPtr<const Matrix> trial_jac_c();
   /** Jacobian of d (at current point) */
   SmartPtr<const Matrix> curr_jac_d();
   /** Jacobian of d (at trial point) */
   SmartPtr<const Matrix> trial_jac_d();
   /** Product of Jacobian (evaluated at current point) of C
    *  transpose with general vector
    */
   SmartPtr<const Vector> curr_jac_cT_times_vec(
      const Vector& vec
   );
   /** Product of Jacobian (evaluated at trial point) of C
    *  transpose with general vector
    */
   SmartPtr<const Vector> trial_jac_cT_times_vec(
      const Vector& vec
   );
   /** Product of Jacobian (evaluated at current point) of D
    *  transpose with general vector
    */
   SmartPtr<const Vector> curr_jac_dT_times_vec(
      const Vector& vec
   );
   /** Product of Jacobian (evaluated at trial point) of D
    *  transpose with general vector
    */
   SmartPtr<const Vector> trial_jac_dT_times_vec(
      const Vector& vec
   );
   /** Product of Jacobian (evaluated at current point) of C
    *  transpose with current y_c
    */
   SmartPtr<const Vector> curr_jac_cT_times_curr_y_c();
   /** Product of Jacobian (evaluated at trial point) of C
    *  transpose with trial y_c
    */
   SmartPtr<const Vector> trial_jac_cT_times_trial_y_c();
   /** Product of Jacobian (evaluated at current point) of D
    *  transpose with current y_d
    */
   SmartPtr<const Vector> curr_jac_dT_times_curr_y_d();
   /** Product of Jacobian (evaluated at trial point) of D
    *  transpose with trial y_d
    */
   SmartPtr<const Vector> trial_jac_dT_times_trial_y_d();
   /** Product of Jacobian (evaluated at current point) of C
    *  with general vector
    */
   SmartPtr<const Vector> curr_jac_c_times_vec(
      const Vector& vec
   );
   /** Product of Jacobian (evaluated at current point) of D
    *  with general vector
    */
   SmartPtr<const Vector> curr_jac_d_times_vec(
      const Vector& vec
   );
   /** Constraint Violation (at current iterate).
    *
    *  This value should
    *  be used in the line search, and not curr_primal_infeasibility().
    *  What type of norm is used depends on constr_viol_normtype
    */
   virtual Number curr_constraint_violation();
   /** Constraint Violation (at trial point).
    *
    *  This value should
    *  be used in the line search, and not curr_primal_infeasibility().
    *  What type of norm is used depends on constr_viol_normtype
    */
   virtual Number trial_constraint_violation();
   /** Real constraint violation in a given norm (at current iterate).
    *
    *  This considers the inequality constraints without slacks.
    */
   virtual Number curr_nlp_constraint_violation(
      ENormType NormType
   );
   /** Unscaled real constraint violation in a given norm (at current iterate).
    *
    *  This considers the inequality constraints without slacks.
    */
   virtual Number unscaled_curr_nlp_constraint_violation(
      ENormType NormType
   );
   /** Unscaled real constraint violation in a given norm (at trial iterate).
    *
    *  This considers the inequality constraints without slacks.
    */
   virtual Number unscaled_trial_nlp_constraint_violation(
      ENormType NormType
   );
   //@}

   /** @name Hessian matrices */
   //@{
   /** exact Hessian at current iterate (uncached) */
   SmartPtr<const SymMatrix> curr_exact_hessian();
   //@}

   /** @name primal-dual error and its components */
   //@{
   /** x-part of gradient of Lagrangian function (at current point) */
   SmartPtr<const Vector> curr_grad_lag_x();
   /** x-part of gradient of Lagrangian function (at trial point) */
   SmartPtr<const Vector> trial_grad_lag_x();
   /** s-part of gradient of Lagrangian function (at current point) */
   SmartPtr<const Vector> curr_grad_lag_s();
   /** s-part of gradient of Lagrangian function (at trial point) */
   SmartPtr<const Vector> trial_grad_lag_s();
   /** x-part of gradient of Lagrangian function (at current point)
    * including linear damping term
    */
   SmartPtr<const Vector> curr_grad_lag_with_damping_x();
   /** s-part of gradient of Lagrangian function (at current point)
    * including linear damping term
    */
   SmartPtr<const Vector> curr_grad_lag_with_damping_s();
   /** Complementarity for x_L (for current iterate) */
   SmartPtr<const Vector> curr_compl_x_L();
   /** Complementarity for x_U (for current iterate) */
   SmartPtr<const Vector> curr_compl_x_U();
   /** Complementarity for s_L (for current iterate) */
   SmartPtr<const Vector> curr_compl_s_L();
   /** Complementarity for s_U (for current iterate) */
   SmartPtr<const Vector> curr_compl_s_U();
   /** Complementarity for x_L (for trial iterate) */
   SmartPtr<const Vector> trial_compl_x_L();
   /** Complementarity for x_U (for trial iterate) */
   SmartPtr<const Vector> trial_compl_x_U();
   /** Complementarity for s_L (for trial iterate) */
   SmartPtr<const Vector> trial_compl_s_L();
   /** Complementarity for s_U (for trial iterate) */
   SmartPtr<const Vector> trial_compl_s_U();
   /** Relaxed complementarity for x_L (for current iterate and current mu) */
   SmartPtr<const Vector> curr_relaxed_compl_x_L();
   /** Relaxed complementarity for x_U (for current iterate and current mu) */
   SmartPtr<const Vector> curr_relaxed_compl_x_U();
   /** Relaxed complementarity for s_L (for current iterate and current mu) */
   SmartPtr<const Vector> curr_relaxed_compl_s_L();
   /** Relaxed complementarity for s_U (for current iterate and current mu) */
   SmartPtr<const Vector> curr_relaxed_compl_s_U();

   /** Primal infeasibility in a given norm (at current iterate). */
   virtual Number curr_primal_infeasibility(
      ENormType NormType
   );
   /** Primal infeasibility in a given norm (at trial point) */
   virtual Number trial_primal_infeasibility(
      ENormType NormType
   );

   /** Dual infeasibility in a given norm (at current iterate) */
   virtual Number curr_dual_infeasibility(
      ENormType NormType
   );
   /** Dual infeasibility in a given norm (at trial iterate) */
   virtual Number trial_dual_infeasibility(
      ENormType NormType
   );
   /** Unscaled dual infeasibility in a given norm (at current iterate) */
   virtual Number unscaled_curr_dual_infeasibility(
      ENormType NormType
   );

   /** Complementarity (for all complementarity conditions together)
    *  in a given norm (at current iterate)
    */
   virtual Number curr_complementarity(
      Number    mu,
      ENormType NormType
   );
   /** Complementarity (for all complementarity conditions together)
    *  in a given norm (at trial iterate)
    */
   virtual Number trial_complementarity(
      Number    mu,
      ENormType NormType
   );
   /** Complementarity (for all complementarity conditions together)
    *  in a given norm (at current iterate) without NLP scaling.
    */
   virtual Number unscaled_curr_complementarity(
      Number    mu,
      ENormType NormType
   );

   /** Centrality measure (in spirit of the -infinity-neighborhood. */
   Number CalcCentralityMeasure(
      const Vector& compl_x_L,
      const Vector& compl_x_U,
      const Vector& compl_s_L,
      const Vector& compl_s_U
   );
   /** Centrality measure at current point */
   virtual Number curr_centrality_measure();

   /** Total optimality error for the original NLP at the current
    *  iterate, using scaling factors based on multipliers.
    *
    *  Note that here the constraint violation is measured without slacks
    *  (nlp_constraint_violation)
    */
   virtual Number curr_nlp_error();
   /** Total optimality error for the original NLP at the current
    *  iterate, but using no scaling based on multipliers, and no
    *  scaling for the NLP.
    *
    *  Note that here the constraint violation
    *  is measured without slacks (nlp_constraint_violation)
    */
   virtual Number unscaled_curr_nlp_error();

   /** Total optimality error for the barrier problem at the
    *  current iterate, using scaling factors based on multipliers.
    */
   virtual Number curr_barrier_error();

   /** Norm of the primal-dual system for a given mu (at current iterate).
    *
    *  The norm is defined as the sum of the 1-norms of
    *  dual infeasibiliy, primal infeasibility, and complementarity,
    *  all divided by the number of elements of the vectors of which
    *  the norm is taken.
    */
   virtual Number curr_primal_dual_system_error(
      Number mu
   );
   /** Norm of the primal-dual system for a given mu (at trial iterate).
    *
    *  The norm is defined as the sum of the 1-norms of
    *  dual infeasibiliy, primal infeasibility, and complementarity,
    *  all divided by the number of elements of the vectors of which
    *  the norm is taken.
    */
   virtual Number trial_primal_dual_system_error(
      Number mu
   );
   //@}

   /** @name Computing fraction-to-the-boundary step sizes */
   //@{
   /** Fraction to the boundary from (current) primal variables x and s
    *  for a given step
    */
   Number primal_frac_to_the_bound(
      Number        tau,
      const Vector& delta_x,
      const Vector& delta_s
   );
   /** Fraction to the boundary from (current) primal variables x and s
    *  for internal (current) step
    */
   Number curr_primal_frac_to_the_bound(
      Number tau
   );
   /** Fraction to the boundary from (current) dual variables z and v
    *  for a given step
    */
   Number dual_frac_to_the_bound(
      Number        tau,
      const Vector& delta_z_L,
      const Vector& delta_z_U,
      const Vector& delta_v_L,
      const Vector& delta_v_U
   );
   /** Fraction to the boundary from (current) dual variables z and v
    *  for a given step, without caching
    */
   Number uncached_dual_frac_to_the_bound(
      Number        tau,
      const Vector& delta_z_L,
      const Vector& delta_z_U,
      const Vector& delta_v_L,
      const Vector& delta_v_U
   );
   /** Fraction to the boundary from (current) dual variables z and v
    *  for internal (current) step
    */
   Number curr_dual_frac_to_the_bound(
      Number tau
   );
   /** Fraction to the boundary from (current) slacks for a given
    *  step in the slacks.
    *
    *  Usually, one will use the
    *  primal_frac_to_the_bound method to compute the primal fraction
    *  to the boundary step size, but if it is cheaper to provide the
    *  steps in the slacks directly (e.g. when the primal step sizes
    *  are only temporary), the this method is more efficient.  This
    *  method does not cache computations.
    */
   Number uncached_slack_frac_to_the_bound(
      Number        tau,
      const Vector& delta_x_L,
      const Vector& delta_x_U,
      const Vector& delta_s_L,
      const Vector& delta_s_U
   );
   //@}

   /** @name Sigma matrices */
   //@{
   SmartPtr<const Vector> curr_sigma_x();
   SmartPtr<const Vector> curr_sigma_s();
   //@}

   /** average of current values of the complementarities */
   Number curr_avrg_compl();
   /** average of trial values of the complementarities */
   Number trial_avrg_compl();

   /** inner_product of current barrier obj. fn. gradient with
    *  current search direction
    */
   Number curr_gradBarrTDelta();

   /** Compute the norm of a specific type of a set of vectors (uncached) */
   Number
   CalcNormOfType(
      ENormType                            NormType,
      std::vector<SmartPtr<const Vector> > vecs
   );

   /** Compute the norm of a specific type of two vectors (uncached) */
   Number
   CalcNormOfType(
      ENormType     NormType,
      const Vector& vec1,
      const Vector& vec2
   );

   /** Norm type used for calculating constraint violation */
   ENormType constr_viol_normtype() const
   {
      return constr_viol_normtype_;
   }

   /** Method returning true if this is a square problem */
   bool IsSquareProblem() const;

   /** Method returning the IpoptNLP object.
    *
    *  This should only be used with care!
    */
   SmartPtr<IpoptNLP>& GetIpoptNLP()
   {
      return ip_nlp_;
   }

   IpoptAdditionalCq& AdditionalCq()
   {
      DBG_ASSERT(IsValid(add_cq_));
      return *add_cq_;
   }

   /** Called by IpoptType to register the options */
   static void RegisterOptions(
      SmartPtr<RegisteredOptions> roptions
   );

private:
   /**@name Default Compiler Generated Methods
    * (Hidden to avoid implicit creation/calling).
    *
    * These methods are not implemented and
    * we do not want the compiler to implement
    * them for us, so we declare them private
    * and do not define them. This ensures that
    * they will not be implicitly created/called.
    */
   //@{
   /** Default Constructor */
   IpoptCalculatedQuantities();

   /** Copy Constructor */
   IpoptCalculatedQuantities(
      const IpoptCalculatedQuantities&
   );

   /** Default Assignment Operator */
   void operator=(
      const IpoptCalculatedQuantities&
   );
   //@}

   /** @name Pointers for easy access to data and NLP information */
   //@{
   /** Ipopt NLP object */
   SmartPtr<IpoptNLP> ip_nlp_;
   /** Ipopt Data object */
   SmartPtr<IpoptData> ip_data_;
   /** Chen-Goldfarb specific calculated quantities */
   SmartPtr<IpoptAdditionalCq> add_cq_;
   //@}

   /** @name Algorithmic Parameters that can be set through the
    *  options list.
    *
    *  Those parameters are initialize by calling the Initialize method.
    */
   //@{
   /** Parameter in formula for computing overall primal-dual
    *  optimality error
    */
   Number s_max_;
   /** Weighting factor for the linear damping term added to the
    *  barrier objective function.
    */
   Number kappa_d_;
   /** fractional movement allowed in bounds */
   Number slack_move_;
   /** Norm type to be used when calculating the constraint violation */
   ENormType constr_viol_normtype_;
   /** Flag indicating whether the TNLP with identical structure has
    *  already been solved before.
    */
   bool warm_start_same_structure_;
   /** Desired value of the barrier parameter */
   Number mu_target_;
   //@}

   /** @name Caches for slacks */
   //@{
   CachedResults<SmartPtr<Vector> > curr_slack_x_L_cache_;
   CachedResults<SmartPtr<Vector> > curr_slack_x_U_cache_;
   CachedResults<SmartPtr<Vector> > curr_slack_s_L_cache_;
   CachedResults<SmartPtr<Vector> > curr_slack_s_U_cache_;
   CachedResults<SmartPtr<Vector> > trial_slack_x_L_cache_;
   CachedResults<SmartPtr<Vector> > trial_slack_x_U_cache_;
   CachedResults<SmartPtr<Vector> > trial_slack_s_L_cache_;
   CachedResults<SmartPtr<Vector> > trial_slack_s_U_cache_;
   Index num_adjusted_slack_x_L_;
   Index num_adjusted_slack_x_U_;
   Index num_adjusted_slack_s_L_;
   Index num_adjusted_slack_s_U_;
   //@}

   /** @name Cached for objective function stuff */
   //@{
   CachedResults<Number> curr_f_cache_;
   CachedResults<Number> trial_f_cache_;
   CachedResults<SmartPtr<const Vector> > curr_grad_f_cache_;
   CachedResults<SmartPtr<const Vector> > trial_grad_f_cache_;
   //@}

   /** @name Caches for barrier function stuff */
   //@{
   CachedResults<Number> curr_barrier_obj_cache_;
   CachedResults<Number> trial_barrier_obj_cache_;
   CachedResults<SmartPtr<const Vector> > curr_grad_barrier_obj_x_cache_;
   CachedResults<SmartPtr<const Vector> > curr_grad_barrier_obj_s_cache_;
   CachedResults<SmartPtr<const Vector> > grad_kappa_times_damping_x_cache_;
   CachedResults<SmartPtr<const Vector> > grad_kappa_times_damping_s_cache_;
   //@}

   /** @name Caches for constraint stuff */
   //@{
   CachedResults<SmartPtr<const Vector> > curr_c_cache_;
   CachedResults<SmartPtr<const Vector> > trial_c_cache_;
   CachedResults<SmartPtr<const Vector> > curr_d_cache_;
   CachedResults<SmartPtr<const Vector> > trial_d_cache_;
   CachedResults<SmartPtr<const Vector> > curr_d_minus_s_cache_;
   CachedResults<SmartPtr<const Vector> > trial_d_minus_s_cache_;
   CachedResults<SmartPtr<const Matrix> > curr_jac_c_cache_;
   CachedResults<SmartPtr<const Matrix> > trial_jac_c_cache_;
   CachedResults<SmartPtr<const Matrix> > curr_jac_d_cache_;
   CachedResults<SmartPtr<const Matrix> > trial_jac_d_cache_;
   CachedResults<SmartPtr<const Vector> > curr_jac_cT_times_vec_cache_;
   CachedResults<SmartPtr<const Vector> > trial_jac_cT_times_vec_cache_;
   CachedResults<SmartPtr<const Vector> > curr_jac_dT_times_vec_cache_;
   CachedResults<SmartPtr<const Vector> > trial_jac_dT_times_vec_cache_;
   CachedResults<SmartPtr<const Vector> > curr_jac_c_times_vec_cache_;
   CachedResults<SmartPtr<const Vector> > curr_jac_d_times_vec_cache_;
   CachedResults<Number> curr_constraint_violation_cache_;
   CachedResults<Number> trial_constraint_violation_cache_;
   CachedResults<Number> curr_nlp_constraint_violation_cache_;
   CachedResults<Number> unscaled_curr_nlp_constraint_violation_cache_;
   CachedResults<Number> unscaled_trial_nlp_constraint_violation_cache_;
   //@}

   /** Cache for the exact Hessian */
   CachedResults<SmartPtr<const SymMatrix> > curr_exact_hessian_cache_;

   /** @name Components of primal-dual error */
   //@{
   CachedResults<SmartPtr<const Vector> > curr_grad_lag_x_cache_;
   CachedResults<SmartPtr<const Vector> > trial_grad_lag_x_cache_;
   CachedResults<SmartPtr<const Vector> > curr_grad_lag_s_cache_;
   CachedResults<SmartPtr<const Vector> > trial_grad_lag_s_cache_;
   CachedResults<SmartPtr<const Vector> > curr_grad_lag_with_damping_x_cache_;
   CachedResults<SmartPtr<const Vector> > curr_grad_lag_with_damping_s_cache_;
   CachedResults<SmartPtr<const Vector> > curr_compl_x_L_cache_;
   CachedResults<SmartPtr<const Vector> > curr_compl_x_U_cache_;
   CachedResults<SmartPtr<const Vector> > curr_compl_s_L_cache_;
   CachedResults<SmartPtr<const Vector> > curr_compl_s_U_cache_;
   CachedResults<SmartPtr<const Vector> > trial_compl_x_L_cache_;
   CachedResults<SmartPtr<const Vector> > trial_compl_x_U_cache_;
   CachedResults<SmartPtr<const Vector> > trial_compl_s_L_cache_;
   CachedResults<SmartPtr<const Vector> > trial_compl_s_U_cache_;
   CachedResults<SmartPtr<const Vector> > curr_relaxed_compl_x_L_cache_;
   CachedResults<SmartPtr<const Vector> > curr_relaxed_compl_x_U_cache_;
   CachedResults<SmartPtr<const Vector> > curr_relaxed_compl_s_L_cache_;
   CachedResults<SmartPtr<const Vector> > curr_relaxed_compl_s_U_cache_;
   CachedResults<Number> curr_primal_infeasibility_cache_;
   CachedResults<Number> trial_primal_infeasibility_cache_;
   CachedResults<Number> curr_dual_infeasibility_cache_;
   CachedResults<Number> trial_dual_infeasibility_cache_;
   CachedResults<Number> unscaled_curr_dual_infeasibility_cache_;
   CachedResults<Number> curr_complementarity_cache_;
   CachedResults<Number> trial_complementarity_cache_;
   CachedResults<Number> curr_centrality_measure_cache_;
   CachedResults<Number> curr_nlp_error_cache_;
   CachedResults<Number> unscaled_curr_nlp_error_cache_;
   CachedResults<Number> curr_barrier_error_cache_;
   CachedResults<Number> curr_primal_dual_system_error_cache_;
   CachedResults<Number> trial_primal_dual_system_error_cache_;
   //@}

   /** @name Caches for fraction to the boundary step sizes */
   //@{
   CachedResults<Number> primal_frac_to_the_bound_cache_;
   CachedResults<Number> dual_frac_to_the_bound_cache_;
   //@}

   /** @name Caches for sigma matrices */
   //@{
   CachedResults<SmartPtr<const Vector> > curr_sigma_x_cache_;
   CachedResults<SmartPtr<const Vector> > curr_sigma_s_cache_;
   //@}

   /** Cache for average of current complementarity */
   CachedResults<Number> curr_avrg_compl_cache_;
   /** Cache for average of trial complementarity */
   CachedResults<Number> trial_avrg_compl_cache_;

   /** Cache for grad barrier obj. fn inner product with step */
   CachedResults<Number> curr_gradBarrTDelta_cache_;

   /** @name Indicator vectors required for the linear damping terms
    *  to handle unbounded solution sets. */
   //@{
   /** Indicator vector for selecting the elements in x that have
    *  only lower bounds.
    */
   SmartPtr<Vector> dampind_x_L_;
   /** Indicator vector for selecting the elements in x that have
    *  only upper bounds.
    */
   SmartPtr<Vector> dampind_x_U_;
   /** Indicator vector for selecting the elements in s that have
    *  only lower bounds.
    */
   SmartPtr<Vector> dampind_s_L_;
   /** Indicator vector for selecting the elements in s that have
    *  only upper bounds.
    */
   SmartPtr<Vector> dampind_s_U_;
   //@}

   /** @name Temporary vectors for intermediate calculations.
    *
    *  We keep these around to avoid unnecessarily many new allocations
    *  of Vectors.
    */
   //@{
   SmartPtr<Vector> tmp_x_;
   SmartPtr<Vector> tmp_s_;
   SmartPtr<Vector> tmp_c_;
   SmartPtr<Vector> tmp_d_;
   SmartPtr<Vector> tmp_x_L_;
   SmartPtr<Vector> tmp_x_U_;
   SmartPtr<Vector> tmp_s_L_;
   SmartPtr<Vector> tmp_s_U_;

   /** Accessor methods for the temporary vectors */
   Vector& Tmp_x();
   Vector& Tmp_s();
   Vector& Tmp_c();
   Vector& Tmp_d();
   Vector& Tmp_x_L();
   Vector& Tmp_x_U();
   Vector& Tmp_s_L();
   Vector& Tmp_s_U();
   //@}

   /** flag indicating if Initialize method has been called (for
    *  debugging)
    */
   bool initialize_called_;

   /** @name Auxiliary functions */
   //@{
   /** Compute new vector containing the slack to a lower bound
    *  (uncached)
    */
   SmartPtr<Vector> CalcSlack_L(
      const Matrix& P,
      const Vector& x,
      const Vector& x_bound
   );
   /** Compute new vector containing the slack to a upper bound
    *  (uncached)
    */
   SmartPtr<Vector> CalcSlack_U(
      const Matrix& P,
      const Vector& x,
      const Vector& x_bound
   );
   /** Compute barrier term at given point
    *  (uncached)
    */
   Number CalcBarrierTerm(
      Number        mu,
      const Vector& slack_x_L,
      const Vector& slack_x_U,
      const Vector& slack_s_L,
      const Vector& slack_s_U
   );

   /** Compute complementarity for slack / multiplier pair */
   SmartPtr<const Vector> CalcCompl(
      const Vector& slack,
      const Vector& mult
   );

   /** Compute fraction to the boundary parameter for lower and upper bounds */
   Number CalcFracToBound(
      const Vector& slack_L,
      Vector&       tmp_L,
      const Matrix& P_L,
      const Vector& slack_U,
      Vector&       tmp_U,
      const Matrix& P_U,
      const Vector& delta,
      Number        tau
   );

   /** Compute the scaling factors for the optimality error. */
   void ComputeOptimalityErrorScaling(
      const Vector& y_c,
      const Vector& y_d,
      const Vector& z_L,
      const Vector& z_U,
      const Vector& v_L,
      const Vector& v_U,
      Number        s_max,
      Number&       s_d,
      Number&       s_c
   );

   /** Check if slacks are becoming too small.
    *
    *  If slacks are becoming too small, they are change.
    *
    *  @return number of corrected slacks
    */
   Index CalculateSafeSlack(
      SmartPtr<Vector>&             slack,
      const SmartPtr<const Vector>& bound,
      const SmartPtr<const Vector>& curr_point,
      const SmartPtr<const Vector>& multiplier
   );

   /** Computes the indicator vectors that can be used to filter out
    *  those entries in the slack_... variables, that correspond to
    *  variables with only lower and upper bounds.
    *
    *  This is required for the linear damping term in the barrier
    *  objective function to handle unbounded solution sets.
    */
   void ComputeDampingIndicators(
      SmartPtr<const Vector>& dampind_x_L,
      SmartPtr<const Vector>& dampind_x_U,
      SmartPtr<const Vector>& dampind_s_L,
      SmartPtr<const Vector>& dampind_s_U
   );

   /** Check if we are in the restoration phase.
    *
    *  @return true, if the ip_nlp is of the type RestoIpoptNLP
    *
    *  @todo We probably want to
    *  handle this more elegant and don't have an explicit dependency
    *  here.  Now I added this because otherwise the caching doesn't
    *  work properly since the restoration phase objective function
    *  depends on the current barrier parameter.
    */
   bool in_restoration_phase();

   //@}
};

} // namespace Ipopt

#endif