Structure updated and intqpipopt files added

1 files changed, 0 insertions, 264 deletions

diff --git a/build/Bonmin/include/coin/BonTNLP2FPNLP.hpp b/build/Bonmin/include/coin/BonTNLP2FPNLP.hpp
deleted file mode 100644
index 82137c9..0000000
--- a/build/Bonmin/include/coin/BonTNLP2FPNLP.hpp
+++ /dev/null
@@ -1,264 +0,0 @@
-// Copyright (C) 2004, International Business Machines and others.
-// All Rights Reserved.
-// This code is published under the Eclipse Public License.
-//
-//
-// Authors:  Pierre Bonami 06/10/2005
-
-#ifndef _TNLP2FPNLP_HPP_
-#define _TNLP2FPNLP_HPP_
-
-#include "IpTNLP.hpp"
-#include "BonTMINLP.hpp"
-#include "IpSmartPtr.hpp"
-#include "BonTypes.hpp"
-
-namespace Bonmin
-{
-  /** This is an adapter class to convert an NLP to a Feasibility Pump NLP
-   *  by changing the objective function to the (2-norm) distance to a point.
-   * The extra function is set_dist_to_point_obj(size_t n, const double *, const int *)
-   */
-  class TNLP2FPNLP : public Ipopt::TNLP
-  {
-  public:
-    /**@name Constructors/Destructors */
-    //@{
-    /** Build using tnlp as source problem.*/
-    TNLP2FPNLP(const Ipopt::SmartPtr<Ipopt::TNLP> tnlp, double objectiveScalingFactor = 100);
-
-    /** Build using tnlp as source problem and using other for all other parameters..*/
-    TNLP2FPNLP(const Ipopt::SmartPtr<TNLP> tnlp, const Ipopt::SmartPtr<TNLP2FPNLP> other);
-
-    /** Default destructor */
-    virtual ~TNLP2FPNLP();
-    //@}
-    void use(Ipopt::SmartPtr<TNLP> tnlp){
-      tnlp_ = GetRawPtr(tnlp);}
-    /**@name Methods to select the objective function and extra constraints*/
-    //@{
-    /// Flag to indicate that we want to use the feasibility pump objective
-    void set_use_feasibility_pump_objective(bool use_feasibility_pump_objective) 
-    { use_feasibility_pump_objective_ = use_feasibility_pump_objective; }
-
-    /** Flag to indicate that we want to use a cutoff constraint
-     *	This constraint has the form f(x) <= (1-epsilon) f(x') */ 
-    void set_use_cutoff_constraint(bool use_cutoff_constraint)
-    { use_cutoff_constraint_ = use_cutoff_constraint; }
-
-    /// Flag to indicate that we want to use a local branching constraint
-    void set_use_local_branching_constraint(bool use_local_branching_constraint)
-    { use_local_branching_constraint_ = use_local_branching_constraint; }
-    //@}
-
-    /**@name Methods to provide the rhs of the extra constraints*/
-    //@{
-    /// Set the cutoff value to use in the cutoff constraint
-    void set_cutoff(Ipopt::Number cutoff);
-
-    /// Set the rhs of the local branching constraint
-    void set_rhs_local_branching_constraint(double rhs_local_branching_constraint)
-    { assert(rhs_local_branching_constraint >= 0);
-      rhs_local_branching_constraint_ = rhs_local_branching_constraint; }
-    //@}
-
-    /**@name Methods to change the objective function*/
-    //@{
-    /** \brief Set the point to which distance is minimized.
-    * The distance is minimize in a subspace define by a subset of coordinates
-     * \param n number of coordinates on which distance is minimized
-     * \param inds indices of the coordinates on which distance is minimized
-     * \param vals values of the point for coordinates in ind
-     */
-    void set_dist_to_point_obj(size_t n, const Ipopt::Number * vals, const Ipopt::Index * inds);
-
-     /** Set the value for sigma */
-     void setSigma(double sigma){
-       assert(sigma >= 0.);
-       sigma_ = sigma;}
-     /** Set the value for lambda*/
-     void setLambda(double lambda){
-       assert(lambda >= 0. && lambda <= 1.);
-       lambda_ = lambda;}
-     /** Set the value for simgma */
-     void setNorm(int norm){
-       assert(norm >0 && norm < 3);
-       norm_ = norm;}
-    //@}
-
-    /**@name methods to gather information about the NLP */
-    //@{
-    /** get info from nlp_ and add hessian information */
-    virtual bool get_nlp_info(Ipopt::Index& n, Ipopt::Index& m, Ipopt::Index& nnz_jac_g,
-        Ipopt::Index& nnz_h_lag, Ipopt::TNLP::IndexStyleEnum& index_style);
-
-    /** This call is just passed onto tnlp_
-     */
-    virtual bool get_bounds_info(Ipopt::Index n, Ipopt::Number* x_l, Ipopt::Number* x_u,
-				 Ipopt::Index m, Ipopt::Number* g_l, Ipopt::Number* g_u);
-
-    /** Passed onto tnlp_
-     */
-    virtual bool get_starting_point(Ipopt::Index n, bool init_x, Ipopt::Number* x,
-        bool init_z, Ipopt::Number* z_L, Ipopt::Number* z_U,
-        Ipopt::Index m, bool init_lambda,
-        Ipopt::Number* lambda)
-    {
-      int m2 = m;
-      if(use_cutoff_constraint_) {
-        m2--;
-        if(lambda!=NULL)lambda[m2] = 0;
-      }
-      if(use_local_branching_constraint_) {
-        m2--;
-        if(lambda!= NULL)lambda[m2] = 0;
-      }
-      int ret_code = tnlp_->get_starting_point(n, init_x, x,
-          init_z, z_L, z_U, m2, init_lambda, lambda);
-      return ret_code;
-    }
-
-    /** overloaded to return the value of the objective function */
-    virtual bool eval_f(Ipopt::Index n, const Ipopt::Number* x, bool new_x,
-        Ipopt::Number& obj_value);
-
-    /** overload this method to return the vector of the gradient of
-     *  the objective w.r.t. x */
-    virtual bool eval_grad_f(Ipopt::Index n, const Ipopt::Number* x, bool new_x,
-        Ipopt::Number* grad_f);
-
-    /** overload to return the values of the left-hand side of the
-        constraints */
-    virtual bool eval_g(Ipopt::Index n, const Ipopt::Number* x, bool new_x,
-			Ipopt::Index m, Ipopt::Number* g);
-
-    /** overload to return the jacobian of g */
-    virtual bool eval_jac_g(Ipopt::Index n, const Ipopt::Number* x, bool new_x,
-			    Ipopt::Index m, Ipopt::Index nele_jac, Ipopt::Index* iRow,
-			    Ipopt::Index *jCol, Ipopt::Number* values);
-
-    /** Evaluate the modified Hessian of the Lagrangian*/
-    virtual bool eval_h(Ipopt::Index n, const Ipopt::Number* x, bool new_x,
-        Ipopt::Number obj_factor, Ipopt::Index m, const Ipopt::Number* lambda,
-        bool new_lambda, Ipopt::Index nele_hess,
-        Ipopt::Index* iRow, Ipopt::Index* jCol, Ipopt::Number* values);
-    //@}
-
-    /** @name Solution Methods */
-    //@{
-    /** This method is called when the algorithm is complete so the TNLP can store/write the solution */
-    virtual void finalize_solution(Ipopt::SolverReturn status,
-        Ipopt::Index n, const Ipopt::Number* x, const Ipopt::Number* z_L, const Ipopt::Number* z_U,
-        Ipopt::Index m, const Ipopt::Number* g, const Ipopt::Number* lambda,
-        Ipopt::Number obj_value,
-        const Ipopt::IpoptData* ip_data,
-        Ipopt::IpoptCalculatedQuantities* ip_cq);
-    //@}
-
-    virtual bool get_variables_linearity(Ipopt::Index n, LinearityType* var_types)
-    {
-      return tnlp_->get_variables_linearity(n, var_types);;
-    }
-
-    /** overload this method to return the constraint linearity.
-     * array should be alocated with length at least n. (default implementation
-     *  just return false and does not fill the array).*/
-    virtual bool get_constraints_linearity(Ipopt::Index m, LinearityType* const_types)
-    {
-      int m2 = m;
-      if(use_cutoff_constraint_) {
-        m2--;
-        const_types[m2] = Ipopt::TNLP::NON_LINEAR;
-      } 
-      if(use_local_branching_constraint_) {
-        m2--;
-        const_types[m2] = Ipopt::TNLP::LINEAR;
-      }
-      return tnlp_->get_constraints_linearity(m2, const_types);
-    }
-    /** @name Scaling of the objective function */
-    //@{
-    void setObjectiveScaling(double value)
-    {
-      objectiveScalingFactor_ = value;
-    }
-    double getObjectiveScaling() const
-    {
-      return objectiveScalingFactor_;
-    }
-
-  private:
-    /** @name Internal methods to help compute the distance, its gradient and hessian */
-    //@{
-    /** Compute the norm-2 distance to the current point to which distance is minimized. */
-    double dist_to_point(const Ipopt::Number *x);
-    //@}
-    /**@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 */
-    TNLP2FPNLP();
-
-    /** Copy Constructor */
-    TNLP2FPNLP(const TNLP2FPNLP&);
-
-    /** Overloaded Equals Operator */
-    void operator=(const TNLP2FPNLP&);
-    //@}
-
-    /** pointer to the tminlp that is being adapted */
-    Ipopt::SmartPtr<TNLP> tnlp_;
-
-    /** @name Data for storing the point the distance to which is minimized */
-    //@{
-    /// Indices of the variables for which distance is minimized (i.e. indices of integer variables in a feasibility pump setting)
-    vector<Ipopt::Index> inds_;
-    /// Values of the point to which we separate (if x is the point vals_[i] should be x[inds_[i]] )
-    vector<Ipopt::Number> vals_;
-    /** value for the convex combination to take between original objective and distance function.
-      * ( take lambda_ * distance + (1-lambda) sigma f(x).*/
-    double lambda_;
-    /** Scaling for the original objective.*/
-    double sigma_;
-   /** Norm to use (L_1 or L_2).*/
-   int norm_;
-    //@}
-
-    /// Scaling factor for the objective
-    double objectiveScalingFactor_;
-
-    /**@name Flags to  select the objective function and extra constraints*/
-    //@{
-    /// Flag to indicate that we want to use the feasibility pump objective
-    bool use_feasibility_pump_objective_;
-
-    /** Flag to indicate that we want to use a cutoff constraint
-     *	This constraint has the form f(x) <= (1-epsilon) f(x') */ 
-    bool use_cutoff_constraint_;    
-
-    /// Flag to indicate that we want to use a local branching constraint
-    bool use_local_branching_constraint_;
-    //@}
-
-    /**@name Data for storing the rhs of the extra constraints*/
-    //@{
-    /// Value of best solution known
-    double cutoff_;
-
-    /// RHS of local branching constraint
-    double rhs_local_branching_constraint_;
-    //@}
-
-    /// Ipopt::Index style (C++ or Fortran)
-    Ipopt::TNLP::IndexStyleEnum index_style_;
-
-  };
-
-} // namespace Ipopt
-
-#endif /*_TNLP2FPNLP_HPP_*/