// Copyright (C) 2004, 2010 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 __IPIPOPTALG_HPP__
#define __IPIPOPTALG_HPP__

#include "IpIpoptNLP.hpp"
#include "IpAlgStrategy.hpp"
#include "IpSearchDirCalculator.hpp"
#include "IpLineSearch.hpp"
#include "IpMuUpdate.hpp"
#include "IpConvCheck.hpp"
#include "IpOptionsList.hpp"
#include "IpIterateInitializer.hpp"
#include "IpIterationOutput.hpp"
#include "IpAlgTypes.hpp"
#include "IpHessianUpdater.hpp"
#include "IpEqMultCalculator.hpp"

namespace Ipopt
{

/** The main ipopt algorithm class.
 *
 *  Main Ipopt algorithm class, contains the main optimize method,
 *  handles the execution of the optimization.
 *  The constructor initializes the data structures through the nlp,
 *  and the Optimize method then assumes that everything is
 *  initialized and ready to go.
 *  After an optimization is complete, the user can access the
 *  solution through the passed in ip_data structure.
 *  Multiple calls to the Optimize method are allowed as long as the
 *  structure of the problem remains the same (i.e. starting point
 *  or nlp parameter changes only).
 */
class IPOPTLIB_EXPORT IpoptAlgorithm: public AlgorithmStrategyObject
{
public:

   /**@name Constructors/Destructors */
   ///@{
   /** Constructor.
    *
    *  The IpoptAlgorithm uses smart pointers for these
    *  passed-in pieces to make sure that a user of IpoptAlgoroithm
    *  cannot pass in an object created on the stack!
    *
    *  The optional linear_solver_name is used for printing.
    */
   IpoptAlgorithm(
      const SmartPtr<SearchDirectionCalculator>& search_dir_calculator,  ///< search direction calculator
      const SmartPtr<LineSearch>&                line_search,            ///< line search
      const SmartPtr<MuUpdate>&                  mu_update,              ///< mu updater
      const SmartPtr<ConvergenceCheck>&          conv_check,             ///< convergence check
      const SmartPtr<IterateInitializer>&        iterate_initializer,    ///< iterate initializer
      const SmartPtr<IterationOutput>&           iter_output,            ///< iteration output
      const SmartPtr<HessianUpdater>&            hessian_updater,        ///< hessian updater
      const SmartPtr<EqMultiplierCalculator>&    eq_multiplier_calculator = NULL,  ///< calculator for multipliers
      const std::string&                         linear_solver_name = ""  ///< name of linear solver @since 3.14.0
   );

   /** Destructor */
   virtual ~IpoptAlgorithm();
   ///@}

   /** overloaded from AlgorithmStrategyObject */
   virtual bool InitializeImpl(
      const OptionsList& options,
      const std::string& prefix
   );

   /** Main solve method. */
   SolverReturn Optimize(
      bool isResto = false
   );

   /** Methods for IpoptType */
   ///@{
   static void RegisterOptions(
      SmartPtr<RegisteredOptions> roptions
   );
   ///@}

   /**@name Access to internal strategy objects */
   ///@{
   SmartPtr<SearchDirectionCalculator> SearchDirCalc()
   {
      return search_dir_calculator_;
   }
   ///@}

   static void print_copyright_message(
      const Journalist& jnlst
   );

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 */
   IpoptAlgorithm();

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

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

   /** @name Strategy objects */
   ///@{
   SmartPtr<SearchDirectionCalculator> search_dir_calculator_;
   SmartPtr<LineSearch> line_search_;
   SmartPtr<MuUpdate> mu_update_;
   SmartPtr<ConvergenceCheck> conv_check_;
   SmartPtr<IterateInitializer> iterate_initializer_;
   SmartPtr<IterationOutput> iter_output_;
   SmartPtr<HessianUpdater> hessian_updater_;
   /** The multiplier calculator (for y_c and y_d) has to be set only
    *  if option recalc_y is set to true
    */
   SmartPtr<EqMultiplierCalculator> eq_multiplier_calculator_;
   ///@}

   /** @name Main steps of the algorithm */
   ///@{
   /** Method for updating the current Hessian.
    *
    *  This can either just evaluate the exact Hessian (based on
    *  the current iterate), or perform a quasi-Newton update.
    */
   void UpdateHessian();

   /** Method to update the barrier parameter.
    *
    *  @return false, if the algorithm can't continue with the
    *  regular procedure and needs to revert to a fallback
    *  mechanism in the line search (such as restoration phase)
    */
   bool UpdateBarrierParameter();

   /** Method to setup the call to the PDSystemSolver.
    *
    *  @return false, if the algorithm can't continue with the regular
    *  procedure and needs to revert to a fallback mechanism in the
    *  line search (such as restoration phase)
    */
   bool ComputeSearchDirection();

   /** Method computing the new iterate (usually vialine search).
    *
    *  The acceptable point is the one in trial after return.
    */
   void ComputeAcceptableTrialPoint();

   /** Method for accepting the trial point as the new iteration,
    *  possibly after adjusting the variable bounds in the NLP.
    */
   void AcceptTrialPoint();

   /** Do all the output for one iteration */
   void OutputIteration();

   /** Sets up initial values for the iterates.
    *
    * Corrects the initial values for x and s (force in bounds)
    */
   void InitializeIterates();

   /** Print the problem size statistics */
   void PrintProblemStatistics();

   /** Compute the Lagrangian multipliers for a feasibility problem */
   void ComputeFeasibilityMultipliers();
   ///@}

   /** @name internal flags */
   ///@{
   /** Flag indicating if the statistic should not be printed */
   bool skip_print_problem_stats_;
   ///@}

   /** @name Algorithmic parameters */
   ///@{
   /** safeguard factor for bound multipliers.
    *
    *  If value >= 1, then
    *  the dual variables will never deviate from the primal estimate
    *  by more than the factors kappa_sigma and 1./kappa_sigma.
    */
   Number kappa_sigma_;
   /** Flag indicating whether the y multipliers should be
    *  recalculated with the eq_mutliplier_calculator object for each
    *  new point.
    */
   bool recalc_y_;
   /** Feasibility threshold for recalc_y */
   Number recalc_y_feas_tol_;
   /** Flag indicating if we want to do Mehrotras's algorithm.
    *
    *  This means that a number of options are ignored, or have to be set
    *  (or are automatically set) to certain values.
    */
   bool mehrotra_algorithm_;
   /** String specifying linear solver */
   std::string linear_solver_name_;
   ///@}

   /** @name auxiliary functions */
   ///@{
   void calc_number_of_bounds(
      const Vector& x,
      const Vector& x_L,
      const Vector& x_U,
      const Matrix& Px_L,
      const Matrix& Px_U,
      Index&        n_tot,
      Index&        n_only_lower,
      Index&        n_both,
      Index&        n_only_upper
   );

   /** Method for ensuring that the trial multipliers are not too far
    *  from the primal estime.
    *
    *  If a correction is made, new_trial_z
    *  is a pointer to the corrected multiplier, and the return value
    *  of this method give the magnitutde of the largest correction
    *  that we done.  If no correction was made, new_trial_z is just
    *  a pointer to trial_z, and the return value is zero.
    */
   Number correct_bound_multiplier(
      const Vector&           trial_z,
      const Vector&           trial_slack,
      const Vector&           trial_compl,
      SmartPtr<const Vector>& new_trial_z
   );
   ///@}
};

} // namespace Ipopt

#endif