cbcintlinprog added

1 files changed, 0 insertions, 114 deletions

diff --git a/newstructure/sci_gateway/cpp/minbndTMINLP.hpp b/newstructure/sci_gateway/cpp/minbndTMINLP.hpp
deleted file mode 100644
index 581d5ce..0000000
--- a/newstructure/sci_gateway/cpp/minbndTMINLP.hpp
+++ /dev/null
@@ -1,114 +0,0 @@
-// Copyright (C) 2016 - IIT Bombay - FOSSEE
-//
-// This file must be used under the terms of the CeCILL.
-// This source file is licensed as described in the file COPYING, which
-// you should have received as part of this distribution.  The terms
-// are also available at
-// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
-// Author: Harpreet Singh
-// Organization: FOSSEE, IIT Bombay
-// Email: toolbox@scilab.in
-
-#ifndef minbndTMINLP_HPP
-#define minbndTMINLP_HPP
-
-#include "BonTMINLP.hpp"
-#include "IpTNLP.hpp"
-#include "call_scilab.h"
-
-using namespace  Ipopt;
-using namespace Bonmin;
-    
-class minbndTMINLP : public TMINLP
-{
-	private:
-
-  	Index numVars_;	            //Number of input variables
-  	
-  	Index intconSize_;
- 
-    Number *lb_= NULL;	 		//lb_ is a pointer to a matrix of size of 1*numVars_ with lower bound of all variables.
-
-    Number *ub_= NULL;	 		//ub_ is a pointer to a matrix of size of 1*numVars_ with upper bound of all variables.
-
-    Number *finalX_= NULL;		//finalX_ is a pointer to a matrix of size of 1*numVars_ with final value for the primal variables.
-
-  	Number finalObjVal_;        //finalObjVal_ is a scalar with the final value of the objective.
-
-    Number *intcon_ = NULL;
-
-  	int status_;			 		//Solver return status
-  	minbndTMINLP(const minbndTMINLP&);
-  	minbndTMINLP& operator=(const minbndTMINLP&);
-
-public:
-	// Constructor
-    	minbndTMINLP(Index nV, Number *lb, Number *ub, Index intconSize, Number *intcon):numVars_(nV),lb_(lb),ub_(ub),intconSize_(intconSize),intcon_(intcon),finalX_(0),finalObjVal_(1e20){	}
-  
-	/** default destructor */
-  	virtual ~minbndTMINLP();
-
-  	virtual bool get_variables_types(Index n, VariableType* var_types);
- 
-    virtual bool get_variables_linearity(Index n, Ipopt::TNLP::LinearityType* var_types);
-
-    virtual bool get_constraints_linearity(Index m, Ipopt::TNLP::LinearityType* const_types);
-  	
-  	/** Method to return some info about the nlp */
-  	virtual bool get_nlp_info(Index& n, Index& m, Index& nnz_jac_g,
-                            Index& nnz_h_lag, TNLP::IndexStyleEnum& index_style);
-
-  	/** Method to return the bounds for my problem */
-  	virtual bool get_bounds_info(Index n, Number* x_l, Number* x_u,
-                               Index m, Number* g_l, Number* g_u);
-
-  	/** Method to return the starting point for the algorithm */
-  	virtual bool get_starting_point(Index n, bool init_x, Number* x,
-                                  bool init_z, Number* z_L, Number* z_U,
-                                  Index m, bool init_lambda,
-                                  Number* lambda);
-
-  	/** Method to return the objective value */
-  	virtual bool eval_f(Index n, const Number* x, bool new_x, Number& obj_value);
-
-  	/** Method to return the gradient of the objective */
-  	virtual bool eval_grad_f(Index n, const Number* x, bool new_x, Number* grad_f);
-
-  	/** Method to return the constraint residuals */
-  	virtual bool eval_g(Index n, const Number* x, bool new_x, Index m, Number* g);
-
-  	/** Method to return:
-  	*   1) The structure of the jacobian (if "values" is NULL)
-   	*   2) The values of the jacobian (if "values" is not NULL)
-   	*/
-  	virtual bool eval_jac_g(Index n, const Number* x, bool new_x,Index m, Index nele_jac, Index* iRow, Index *jCol,Number* values);
-
-  	/** Method to return:
-   	*   1) The structure of the hessian of the lagrangian (if "values" is NULL)
-   	*   2) The values of the hessian of the lagrangian (if "values" is not NULL)
-   	*/
-  	virtual bool eval_h(Index n, const Number* x, bool new_x,Number obj_factor, Index m, const Number* lambda,bool new_lambda, Index nele_hess, Index* iRow,Index* jCol, Number* values);
-
-  	/** This method is called when the algorithm is complete so the TNLP can store/write the solution */
-  	virtual void finalize_solution(SolverReturn status,Index n, const Number* x, Number obj_value);
-  	
-  	virtual const SosInfo * sosConstraints() const{return NULL;}
-    virtual const BranchingInfo* branchingInfo() const{return NULL;}
-  
-  	const double * getX();		//Returns a pointer to a matrix of size of 1*numVars_ 
-					//with final value for the primal variables.
-  
-  	const double * getGrad();       //Returns a pointer to a matrix of size of 1*numVars_ 
-					//with final value of gradient for the primal variables.
-
-  	const double * getHess();       //Returns a pointer to a matrix of size of numVars_*numVars_ 
-					//with final value of hessian for the primal variables.
-
-  	double getObjVal();		//Returns the output of the final value of the objective.
-
-  	double iterCount();		//Returns the iteration count
-
-  	int returnStatus();		//Returns the status count
-};
-
-#endif