C++ Example NLP for interfacing a problem with IPOPT. More...
#include <MyNLP.hpp>
Public Member Functions | |
MyNLP () | |
default constructor | |
virtual | ~MyNLP () |
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). | |
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. | |
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++") | |
MyNLP (const MyNLP &) | |
MyNLP & | operator= (const MyNLP &) |
Overloaded Equals Operator. |
C++ Example NLP for interfacing a problem with IPOPT.
MyNLP implements a C++ example showing how to interface with IPOPT through the TNLP interface. This example is designed to go along with the tutorial document (see Examples/CppTutorial/). This class implements the following NLP.
min_x f(x) = -(x2-2)^2 s.t. 0 = x1^2 + x2 - 1 -1 <= x1 <= 1
Definition at line 28 of file MyNLP.hpp.
MyNLP::MyNLP | ( | ) |
default constructor
virtual MyNLP::~MyNLP | ( | ) | [virtual] |
default destructor
MyNLP::MyNLP | ( | const MyNLP & | ) | [private] |
virtual bool MyNLP::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 MyNLP::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 MyNLP::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.
Method to return the objective value.
Implements Ipopt::TNLP.
virtual bool MyNLP::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.
Method to return the constraint residuals.
Implements Ipopt::TNLP.
virtual bool MyNLP::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 MyNLP::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 MyNLP::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.
Overloaded Equals Operator.
Reimplemented from Ipopt::TNLP.