cbcintlinprog added

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diff --git a/newstructure/thirdparty/linux/include/coin/BonTMINLPLinObj.hpp b/newstructure/thirdparty/linux/include/coin/BonTMINLPLinObj.hpp
deleted file mode 100644
index 819bc57..0000000
--- a/newstructure/thirdparty/linux/include/coin/BonTMINLPLinObj.hpp
+++ /dev/null
@@ -1,216 +0,0 @@
-// (C) Copyright International Business Machines Corporation 2007
-// All Rights Reserved.
-//
-// Authors :
-// Pierre Bonami, International Business Machines Corporation
-//
-// Date : 08/16/2007
-
-
-#ifndef TMINLPLinObj_H
-#define TMINLPLinObj_H
-
-#include "BonTMINLP.hpp"
-
-namespace Bonmin {
-/** From a TMINLP, this class adapts to another TMINLP where the original objective is transformed into a constraint
-    by adding an extra variable which is minimized.
-
-    More precisely 
-    \f[
-    \begin{array}{l}
-    \min f(x)\\
-    s.t\\
-    g_l \leq g(x) \leq g_u\\
-    x_l \leq x \leq u
-    \end{array}
-    \f]
-    is transformed ino
-    \begin{array}{l}
-    \min \eta\\
-    s.t\\
-    -\infty \leq f(x) - \eta \leq 0\\
-    g_l \leq g(x) \leq g_u\\
-    x_l \leq x \leq u
-    \end{array}
-    \f]
-    The objective is put as first constraint of the problem and the extra variable is the last one.
- .*/
-class TMINLPLinObj: public Bonmin::TMINLP {
-  public:
-   /** Default constructor*/
-   TMINLPLinObj();
-
-  /** destructor.*/
-  virtual ~TMINLPLinObj();
-
-  /** set reference TMINLP */
-  void setTminlp(Ipopt::SmartPtr<TMINLP> tminlp);
-  
-    /**@name methods to gather information about the MINLP */
-    //@{
-    /** Return the number of variables
-     *  and constraints, and the number of non-zeros in the jacobian and
-     *  the hessian. Call tminlp_ one  but number of constraints and non-zeroes in the jacobian is stored internally.*/
-        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);
-    /** Return scaling parameters. If tminlp_ method returns true, translate
-      * constraint scaling (if asked).
-     */
-    virtual bool get_scaling_parameters(Ipopt::Number& obj_scaling,
-                                        bool& use_x_scaling, Ipopt::Index n,
-                                        Ipopt::Number* x_scaling,
-                                        bool& use_g_scaling, Ipopt::Index m,
-                                        Ipopt::Number* g_scaling);
-
-
-    /** Get the variable type. Just call tminlp_'s method;. */
-    virtual bool get_variables_types(Ipopt::Index n, VariableType* var_types){
-      assert(IsValid(tminlp_));
-      assert(n == n_);
-      var_types[n-1] = TMINLP::CONTINUOUS;
-      return tminlp_->get_variables_types(n - 1, var_types);
-    }
-
-    /** Return the constraints linearity. Call tminlp_'s method and translate.
-      */
-    virtual bool get_constraints_linearity(Ipopt::Index m, 
-					   Ipopt::TNLP::LinearityType* const_types);
-
-    /** Return the information about the bound
-     *  on the variables and constraints. Call tminlp_'s method and translate
-     *  constraints bounds.*/
-    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);
-
-    /** Return the starting point. 
-        Have to translate z_L and z_U.
-     */
-    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);
-
-    /** Return the value of the objective function.
-      * Just call tminlp_ method. */
-    virtual bool eval_f(Ipopt::Index n, const Ipopt::Number* x, bool new_x,
-        Ipopt::Number& obj_value){
-        assert(n == n_);
-        obj_value = x[n-1];
-       return true;}
-
-    /** Return the vector of the gradient of
-     *  the objective w.r.t. x. Just call tminlp_ method. */
-    virtual bool eval_grad_f(Ipopt::Index n, const Ipopt::Number* x, bool new_x,
-        Ipopt::Number* grad_f){
-       assert(IsValid(tminlp_));
-       assert(n == n_);
-       n--;
-       for(int  i = 0 ; i < n ; i++){
-        grad_f[i] = 0;}
-       grad_f[n] = 1;
-       return true;}
-
-    /** Return the vector of constraint values.
-      * Use tminlp_ functions and use mapping to get the needed values. */
-    virtual bool eval_g(Ipopt::Index n, const Ipopt::Number* x, bool new_x,
-        Ipopt::Index m, Ipopt::Number* g);
-
-    /** Return the jacobian of the constraints. 
-      * In first call nothing to change. In later just fix the values for the simple concaves
-      * and remove entries corresponding to nonConvex constraints. */
-    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);
-
-    /** \brief Return the hessian of the lagrangian. 
-      * Here we just put lambda in the correct format and call
-      * tminlp_'s function.*/
-    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);
-    /** Compute the value of a single constraint. The constraint
-     *  number is i (starting counting from 0. */
-    virtual bool eval_gi(Ipopt::Index n, const Ipopt::Number* x, bool new_x,
-			 Ipopt::Index i, Ipopt::Number& gi);
-    /** Compute the structure or values of the gradient for one
-     *  constraint. The constraint * number is i (starting counting
-     *  from 0.  Other things are like with eval_jac_g. */
-    virtual bool eval_grad_gi(Ipopt::Index n, const Ipopt::Number* x, bool new_x,
-			      Ipopt::Index i, Ipopt::Index& nele_grad_gi, Ipopt::Index* jCol,
-			      Ipopt::Number* values);
-    //@}
-   
-    virtual bool get_variables_linearity(Ipopt::Index n, Ipopt::TNLP::LinearityType* c){
-      assert(IsValid(tminlp_));
-      assert(n == n_);
-      bool r_val = tminlp_->get_variables_linearity(n-1, c);
-      c[n - 1] = Ipopt::TNLP::LINEAR;
-      return r_val;
-    }
-
-
-    /** @name Solution Methods */
-    //@{
-     /**  Use tminlp_ function.*/
-    virtual void finalize_solution(TMINLP::SolverReturn status,
-                                   Ipopt::Index n, const Ipopt::Number* x, Ipopt::Number obj_value){
-       return tminlp_->finalize_solution(status, n - 1, x,
-                                  obj_value);
-    }
-    //@}
-    
-     /**  Use tminlp_ function.*/
-    virtual const BranchingInfo * branchingInfo() const{
-      return tminlp_->branchingInfo();
-    }
-
-     /**  Use tminlp_ function.
-          \bug Has to translate sos information.*/
-    virtual const SosInfo * sosConstraints() const{
-      return tminlp_->sosConstraints();
-    }
-     /**  Use tminlp_ function.*/
-    virtual const PerturbInfo* perturbInfo() const
-    {
-      return tminlp_->perturbInfo();
-    }
-
-    /**  Use tminlp_ function.*/
-    virtual bool hasUpperBoundingObjective(){
-      assert(IsValid(tminlp_));
-      return tminlp_->hasUpperBoundingObjective();}
-    
-    /** Use tminlp_ function.*/
-    virtual bool eval_upper_bound_f(Ipopt::Index n, const Ipopt::Number* x,
-                                    Ipopt::Number& obj_value){
-       assert(IsValid(tminlp_));
-       return tminlp_->eval_upper_bound_f(n - 1, x, obj_value); }
-
-  /** Say if problem has a linear objective (for OA) */
-  virtual bool hasLinearObjective(){return true;}
-  /** return pointer to tminlp_.*/
-  Ipopt::SmartPtr<TMINLP> tminlp(){return tminlp_;}
-  private:
-  /** Reset all data.*/
-   void gutsOfDestructor();
-
-  /** Reference TMINLP which is to be relaxed.*/
-  Ipopt::SmartPtr<TMINLP> tminlp_;
-  /** Ipopt::Number of constraints in the transformed MINLP.*/
-  int m_;
-  /** Ipopt::Number of variables in the transformed MINLP.*/
-  int n_;
-  /** number of non-zeroes in the jacobian of the transformed MINLP.*/
-  int nnz_jac_;
-  /** offset for jacobian.*/
-  int offset_;
-   
-};
-
-
-}/* Ends Bonmin namepsace.*/
-
-#endif
-