#include <TutorialCpp_nlp.hpp>
Public Member Functions | |
TutorialCpp_NLP (Index N, const Number *a) | |
constructor that takes in problem data | |
virtual | ~TutorialCpp_NLP () |
default destructor | |
TutorialCpp_NLP (Index N, const Number *a) | |
constructor that takes in problem data | |
virtual | ~TutorialCpp_NLP () |
default destructor | |
TutorialCpp_NLP (Index N, const Number *a) | |
constructor that takes in problem data | |
virtual | ~TutorialCpp_NLP () |
default destructor | |
Overloaded from TNLP | |
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. | |
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. | |
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. | |
virtual bool | eval_f (Index n, const Number *x, bool new_x, Number &obj_value) |
Method to return the objective value. | |
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_g (Index n, const Number *x, bool new_x, Index m, Number *g) |
Method to return the constraint residuals. | |
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 jacobian (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) |
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 | 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. | |
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. | |
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. | |
virtual bool | eval_f (Index n, const Number *x, bool new_x, Number &obj_value) |
Method to return the objective value. | |
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_g (Index n, const Number *x, bool new_x, Index m, Number *g) |
Method to return the constraint residuals. | |
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 jacobian (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) |
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 | 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. | |
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. | |
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. | |
virtual bool | eval_f (Index n, const Number *x, bool new_x, Number &obj_value) |
Method to return the objective value. | |
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_g (Index n, const Number *x, bool new_x, Index m, Number *g) |
Method to return the constraint residuals. | |
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 jacobian (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) |
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) | |
Solution Methods | |
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. | |
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. | |
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. | |
Private Member Functions | |
Methods to block default compiler methods. | |
The compiler automatically generates the following three methods. Since the default compiler implementation is generally not what you want (for all but the most simple classes), we usually put the declarations of these methods in the private section and never implement them. This prevents the compiler from implementing an incorrect "default" behavior without us knowing. (See Scott Meyers book, "Effective C++") | |
TutorialCpp_NLP () | |
TutorialCpp_NLP (const TutorialCpp_NLP &) | |
TutorialCpp_NLP & | operator= (const TutorialCpp_NLP &) |
TutorialCpp_NLP () | |
TutorialCpp_NLP (const TutorialCpp_NLP &) | |
TutorialCpp_NLP & | operator= (const TutorialCpp_NLP &) |
TutorialCpp_NLP () | |
TutorialCpp_NLP (const TutorialCpp_NLP &) | |
TutorialCpp_NLP & | operator= (const TutorialCpp_NLP &) |
Private Attributes | |
NLP data | |
Index | N_ |
Number of variables. | |
Number * | a_ |
Value of constants in constraints. |
Definition at line 34 of file TutorialCpp_nlp.hpp.
constructor that takes in problem data
virtual TutorialCpp_NLP::~TutorialCpp_NLP | ( | ) | [virtual] |
default destructor
TutorialCpp_NLP::TutorialCpp_NLP | ( | ) | [private] |
TutorialCpp_NLP::TutorialCpp_NLP | ( | const TutorialCpp_NLP & | ) | [private] |
constructor that takes in problem data
virtual TutorialCpp_NLP::~TutorialCpp_NLP | ( | ) | [virtual] |
default destructor
TutorialCpp_NLP::TutorialCpp_NLP | ( | ) | [private] |
TutorialCpp_NLP::TutorialCpp_NLP | ( | const TutorialCpp_NLP & | ) | [private] |
constructor that takes in problem data
virtual TutorialCpp_NLP::~TutorialCpp_NLP | ( | ) | [virtual] |
default destructor
TutorialCpp_NLP::TutorialCpp_NLP | ( | ) | [private] |
TutorialCpp_NLP::TutorialCpp_NLP | ( | const TutorialCpp_NLP & | ) | [private] |
virtual bool TutorialCpp_NLP::get_nlp_info | ( | Index & | n, |
Index & | m, | ||
Index & | nnz_jac_g, | ||
Index & | nnz_h_lag, | ||
IndexStyleEnum & | index_style | ||
) | [virtual] |
Method to return some info about the nlp.
Implements Ipopt::TNLP.
virtual bool TutorialCpp_NLP::get_bounds_info | ( | Index | n, |
Number * | x_l, | ||
Number * | x_u, | ||
Index | m, | ||
Number * | g_l, | ||
Number * | g_u | ||
) | [virtual] |
Method to return the bounds for my problem.
Implements Ipopt::TNLP.
virtual bool TutorialCpp_NLP::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 | ||
) | [virtual] |
Method to return the starting point for the algorithm.
Implements Ipopt::TNLP.
virtual bool TutorialCpp_NLP::eval_f | ( | Index | n, |
const Number * | x, | ||
bool | new_x, | ||
Number & | obj_value | ||
) | [virtual] |
Method to return the objective value.
Implements Ipopt::TNLP.
virtual bool TutorialCpp_NLP::eval_grad_f | ( | Index | n, |
const Number * | x, | ||
bool | new_x, | ||
Number * | grad_f | ||
) | [virtual] |
Method to return the gradient of the objective.
Implements Ipopt::TNLP.
virtual bool TutorialCpp_NLP::eval_g | ( | Index | n, |
const Number * | x, | ||
bool | new_x, | ||
Index | m, | ||
Number * | g | ||
) | [virtual] |
Method to return the constraint residuals.
Implements Ipopt::TNLP.
virtual bool TutorialCpp_NLP::eval_jac_g | ( | Index | n, |
const Number * | x, | ||
bool | new_x, | ||
Index | m, | ||
Index | nele_jac, | ||
Index * | iRow, | ||
Index * | jCol, | ||
Number * | values | ||
) | [virtual] |
Method to return: 1) The structure of the jacobian (if "values" is NULL) 2) The values of the jacobian (if "values" is not NULL)
Implements Ipopt::TNLP.
virtual bool TutorialCpp_NLP::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 | ||
) | [virtual] |
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)
Reimplemented from Ipopt::TNLP.
virtual void TutorialCpp_NLP::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 | ||
) | [virtual] |
This method is called when the algorithm is complete so the TNLP can store/write the solution.
Implements Ipopt::TNLP.
TutorialCpp_NLP& TutorialCpp_NLP::operator= | ( | const TutorialCpp_NLP & | ) | [private] |
virtual bool TutorialCpp_NLP::get_nlp_info | ( | Index & | n, |
Index & | m, | ||
Index & | nnz_jac_g, | ||
Index & | nnz_h_lag, | ||
IndexStyleEnum & | index_style | ||
) | [virtual] |
Method to return some info about the nlp.
Implements Ipopt::TNLP.
virtual bool TutorialCpp_NLP::get_bounds_info | ( | Index | n, |
Number * | x_l, | ||
Number * | x_u, | ||
Index | m, | ||
Number * | g_l, | ||
Number * | g_u | ||
) | [virtual] |
Method to return the bounds for my problem.
Implements Ipopt::TNLP.
virtual bool TutorialCpp_NLP::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 | ||
) | [virtual] |
Method to return the starting point for the algorithm.
Implements Ipopt::TNLP.
virtual bool TutorialCpp_NLP::eval_f | ( | Index | n, |
const Number * | x, | ||
bool | new_x, | ||
Number & | obj_value | ||
) | [virtual] |
Method to return the objective value.
Implements Ipopt::TNLP.
virtual bool TutorialCpp_NLP::eval_grad_f | ( | Index | n, |
const Number * | x, | ||
bool | new_x, | ||
Number * | grad_f | ||
) | [virtual] |
Method to return the gradient of the objective.
Implements Ipopt::TNLP.
virtual bool TutorialCpp_NLP::eval_g | ( | Index | n, |
const Number * | x, | ||
bool | new_x, | ||
Index | m, | ||
Number * | g | ||
) | [virtual] |
Method to return the constraint residuals.
Implements Ipopt::TNLP.
virtual bool TutorialCpp_NLP::eval_jac_g | ( | Index | n, |
const Number * | x, | ||
bool | new_x, | ||
Index | m, | ||
Index | nele_jac, | ||
Index * | iRow, | ||
Index * | jCol, | ||
Number * | values | ||
) | [virtual] |
Method to return: 1) The structure of the jacobian (if "values" is NULL) 2) The values of the jacobian (if "values" is not NULL)
Implements Ipopt::TNLP.
virtual bool TutorialCpp_NLP::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 | ||
) | [virtual] |
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)
Reimplemented from Ipopt::TNLP.
virtual void TutorialCpp_NLP::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 | ||
) | [virtual] |
This method is called when the algorithm is complete so the TNLP can store/write the solution.
Implements Ipopt::TNLP.
TutorialCpp_NLP& TutorialCpp_NLP::operator= | ( | const TutorialCpp_NLP & | ) | [private] |
virtual bool TutorialCpp_NLP::get_nlp_info | ( | Index & | n, |
Index & | m, | ||
Index & | nnz_jac_g, | ||
Index & | nnz_h_lag, | ||
IndexStyleEnum & | index_style | ||
) | [virtual] |
Method to return some info about the nlp.
Implements Ipopt::TNLP.
virtual bool TutorialCpp_NLP::get_bounds_info | ( | Index | n, |
Number * | x_l, | ||
Number * | x_u, | ||
Index | m, | ||
Number * | g_l, | ||
Number * | g_u | ||
) | [virtual] |
Method to return the bounds for my problem.
Implements Ipopt::TNLP.
virtual bool TutorialCpp_NLP::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 | ||
) | [virtual] |
Method to return the starting point for the algorithm.
Implements Ipopt::TNLP.
virtual bool TutorialCpp_NLP::eval_f | ( | Index | n, |
const Number * | x, | ||
bool | new_x, | ||
Number & | obj_value | ||
) | [virtual] |
Method to return the objective value.
Implements Ipopt::TNLP.
virtual bool TutorialCpp_NLP::eval_grad_f | ( | Index | n, |
const Number * | x, | ||
bool | new_x, | ||
Number * | grad_f | ||
) | [virtual] |
Method to return the gradient of the objective.
Implements Ipopt::TNLP.
virtual bool TutorialCpp_NLP::eval_g | ( | Index | n, |
const Number * | x, | ||
bool | new_x, | ||
Index | m, | ||
Number * | g | ||
) | [virtual] |
Method to return the constraint residuals.
Implements Ipopt::TNLP.
virtual bool TutorialCpp_NLP::eval_jac_g | ( | Index | n, |
const Number * | x, | ||
bool | new_x, | ||
Index | m, | ||
Index | nele_jac, | ||
Index * | iRow, | ||
Index * | jCol, | ||
Number * | values | ||
) | [virtual] |
Method to return: 1) The structure of the jacobian (if "values" is NULL) 2) The values of the jacobian (if "values" is not NULL)
Implements Ipopt::TNLP.
virtual bool TutorialCpp_NLP::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 | ||
) | [virtual] |
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)
Reimplemented from Ipopt::TNLP.
virtual void TutorialCpp_NLP::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 | ||
) | [virtual] |
This method is called when the algorithm is complete so the TNLP can store/write the solution.
Implements Ipopt::TNLP.
TutorialCpp_NLP& TutorialCpp_NLP::operator= | ( | const TutorialCpp_NLP & | ) | [private] |
Index TutorialCpp_NLP::N_ [private] |
Number of variables.
Definition at line 118 of file TutorialCpp_nlp.hpp.
Number * TutorialCpp_NLP::a_ [private] |
Value of constants in constraints.
Definition at line 120 of file TutorialCpp_nlp.hpp.