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7 #ifndef __PARAMETRICTNLPEXAMPLE_HPP__
8 #define __PARAMETRICTNLPEXAMPLE_HPP__
15 class ParametricTNLP :
public TNLP
85 const IpoptData* ip_data,
86 IpoptCalculatedQuantities* ip_cq);
virtual bool eval_g(Index n, const Number *x, bool new_x, Index m, Number *g)
Method to return the constraint residuals.
virtual bool get_var_con_metadata(Index n, StringMetaDataMapType &var_string_md, IntegerMetaDataMapType &var_integer_md, NumericMetaDataMapType &var_numeric_md, Index m, StringMetaDataMapType &con_string_md, IntegerMetaDataMapType &con_integer_md, NumericMetaDataMapType &con_numeric_md)
overload this method to return any meta data for the variables and the constraints
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)
Method to return: 1) The structure of the hessian of the lagrangian (if "values" is NULL) 2) The valu...
double Number
Type for all number.
std::map< std::string, std::vector< Index > > IntegerMetaDataMapType
virtual void finalize_metadata(Index n, const StringMetaDataMapType &var_string_md, const IntegerMetaDataMapType &var_integer_md, const NumericMetaDataMapType &var_numeric_md, Index m, const StringMetaDataMapType &con_string_md, const IntegerMetaDataMapType &con_integer_md, const NumericMetaDataMapType &con_numeric_md)
This method is called just before finalize solution.
virtual bool eval_grad_f(Index n, const Number *x, bool new_x, Number *grad_f)
Method to return the gradient of the objective.
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 jacobian (if "values" is NULL) 2) The values of the jacobia...
Number * x
Input: Starting point Output: Optimal solution.
Number Number Index Number Number Index Index nele_hess
Number of non-zero elements in Hessian of Lagrangian.
Number Number Index Number Number Index nele_jac
Number of non-zero elements in constraint Jacobian.
ParametricTNLP & operator=(const ParametricTNLP &)
virtual bool eval_f(Index n, const Number *x, bool new_x, Number &obj_value)
Method to return the objective value.
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 starting point for the algorithm.
std::map< std::string, std::vector< Number > > NumericMetaDataMapType
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 bounds for my problem.
Number eta_2_perturbed_value_
std::map< std::string, std::vector< std::string > > StringMetaDataMapType
virtual ~ParametricTNLP()
default destructor
Number Number * g
Values of constraint at final point (output only - ignored if set to NULL)
virtual bool get_nlp_info(Index &n, Index &m, Index &nnz_jac_g, Index &nnz_h_lag, IndexStyleEnum &index_style)
Method to return some info about the nlp.
IndexStyleEnum
overload this method to return the number of variables and constraints, and the number of non-zeros i...
Number eta_1_perturbed_value_
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)
This method is called when the algorithm is complete so the TNLP can store/write the solution.
SolverReturn
enum for the return from the optimize algorithm (obviously we need to add more)
int Index
Type for all incides.
Number Number Index Number Number Index Index Index index_style
indexing style for iRow & jCol, 0 for C style, 1 for Fortran style
ParametricTNLP()
default constructor
Number Number Index m
Number of constraints.