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// Copyright (C) 2015 - IIT Bombay - FOSSEE
//
// Author: R.Vidyadhar & Vignesh Kannan
// Organization: FOSSEE, IIT Bombay
// Email: rvidhyadar@gmail.com & vignesh2496@gmail.com
// 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
#ifndef __minconNLP_HPP__
#define __minconNLP_HPP__
#include "IpTNLP.hpp"
using namespace Ipopt;
class minconNLP : public TNLP
{
private:
Index numVars_; //Number of input variables
Index numConstr_; //Number of constraints
Number nonlinCon_; //Number of non-linear constraints
Number nonlinIneqCon_; //Number of non-linear inequality constraints
const Number *A_; //Matrix for linear inequality constraints
const Number *b_; //Matrix for bounds of linear inequality constraints
const Number *Aeq_; //Matrix for linear equality constraints
const Number *beq_; //Matrix for bounds of linear equality constraints
Index Arows_; //Number of rows of linear inequality constraints
Index Acols_; //Number of columns of linear inequality constraints
Index brows_; //Number of rows of bounds of linear inequality constraints
Index bcols_; //Number of columns of bounds of linear inequality constraints
Index Aeqrows_; //Number of rows of linear equality constraints
Index Aeqcols_; //Number of columns of linear equality constraints
Index beqrows_; //Number of rows of bounds of linear equality constraints
Index beqcols_; //Number of columns of bounds of linear equality constraints
const Number *varGuess_; //varGuess_ is a pointer to a matrix of size of 1*numVars_
//with initial guess of all variables.
const Number *varUB_; //varUB_ is a pointer to a matrix of size of 1*numVar_
// with upper bounds of all variables.
const Number *varLB_; //varLB_ is a pointer to a matrix of size of 1*numVar_
// with lower bounds of all variables.
Number *finalZl_; //finalZl_ is a pointer to a matrix of size of 1*numVar_
// with final values for the lower bound multipliers
Number *finalZu_; //finalZu_ is a pointer to a matrix of size of 1*numVar_
// with final values for the upper bound multipliers
Number *finalLambda_; //finalLambda_ is a pointer to a matrix of size of 1*numConstr_
// with final values for the upper bound multipliers
Number *finalX_; //finalX_ is a pointer to a matrix of size of 1*numVars_
//with final value for the primal variables.
Number *finalGradient_; //finalGradient_ is a pointer to a matrix of size of numVars_*numVars_
//with final value of gradient for the primal variables.
Number *finalHessian_; //finalHessian_ is a pointer to a matrix of size of 1*numVar_
//with final value of hessian for the primal variables.
Number finalObjVal_; //finalObjVal_ is a scalar with the final value of the objective.
int status_; //Solver return status
minconNLP(const minconNLP&);
minconNLP& operator=(const minconNLP&);
public:
/** user defined constructor */
minconNLP(Index nV, Index nC, Number *x0 ,Number *A, Number *b, Number* Aeq, Number *beq, Index Arows, Index Acols, Index brows, Index bcols, Index Aeqrows, Index Aeqcols, Index beqrows, Index beqcols, Number* LB, Number* UB, Number nlC, Number nlIC) : numVars_(nV), numConstr_(nC), varGuess_(x0), A_(A), b_(b), Aeq_(Aeq), beq_(beq), Arows_(Arows), Acols_(Acols), brows_(brows), bcols_(bcols), Aeqrows_(Aeqrows), Aeqcols_(Aeqcols), beqrows_(beqrows), beqcols_(beqcols), varLB_(LB), varUB_(UB), nonlinCon_(nlC), nonlinIneqCon_(nlIC), finalX_(0), finalZl_(0), finalZu_(0), finalGradient_(0), finalHessian_(0), finalObjVal_(1e20){ }
/** default destructor */
virtual ~minconNLP();
/** 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, 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, const Number* z_L, const Number* z_U,Index m, const Number* g, const Number* lambda,Number obj_value,const IpoptData* ip_data,IpoptCalculatedQuantities* ip_cq);
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.
const double * getZl(); //Returns a pointer to a matrix of size of 1*numVars_
// with final values for the lower bound multipliers
const double * getZu(); //Returns a pointer to a matrix of size of 1*numVars_
//with final values for the upper bound multipliers
const double * getLambda(); //Returns a pointer to a matrix of size of 1*numConstr_
//with final values for the constraint multipliers
double getObjVal(); //Returns the output of the final value of the objective.
int returnStatus(); //Returns the status count
};
#endif
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