#include <TNLP2FPNLP.hpp>
Inheritance diagram for Ipopt::TNLP2FPNLP:
Public Member Functions | |
Constructors/Destructors | |
TNLP2FPNLP (const SmartPtr< TNLP > tnlp, double objectiveScalingFactor=100) | |
virtual | ~TNLP2FPNLP () |
Default destructor. | |
Methods to change the objective function | |
void | set_dist2point_obj (int n, const Number *vals, const Index *inds) |
Set the point to which distance is minimized. | |
methods to gather information about the NLP | |
virtual bool | get_nlp_info (Index &n, Index &m, Index &nnz_jac_g, Index &nnz_h_lag, TNLP::IndexStyleEnum &index_style) |
get info from nlp_ and add hessian information | |
virtual bool | get_bounds_info (Index n, Number *x_l, Number *x_u, Index m, Number *g_l, Number *g_u) |
This call is just passed onto tnlp_. | |
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) |
Passed onto tnlp_. | |
virtual bool | eval_f (Index n, const Number *x, bool new_x, Number &obj_value) |
overloaded to return the value of the objective function | |
virtual bool | eval_grad_f (Index n, const Number *x, bool new_x, Number *grad_f) |
overload this method to return the vector of the gradient of the objective w.r.t. | |
virtual bool | eval_g (Index n, const Number *x, bool new_x, Index m, Number *g) |
passed onto tnlp_ | |
virtual bool | eval_jac_g (Index n, const Number *x, bool new_x, Index m, Index nele_jac, Index *iRow, Index *jCol, Number *values) |
Passed onto tnlp_. | |
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) |
Evaluate the modified Hessian of the Lagrangian. | |
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) |
This method is called when the algorithm is complete so the TNLP can store/write the solution. | |
Scaling of the objective function | |
void | setObjectiveScaling (double value) |
double | getObjectiveScaling () const |
Private Member Functions | |
Internal methods to help compute the distance, its gradient and hessian | |
double | dist2point (const Number *x) |
Compute the norm-2 distance to the current point to which distance is minimized. | |
Default Compiler Generated Methods | |
(Hidden to avoid implicit creation/calling). These methods are not implemented and we do not want the compiler to implement them for us, so we declare them private and do not define them. This ensures that they will not be implicitly created/called. | |
TNLP2FPNLP () | |
Default Constructor. | |
TNLP2FPNLP (const TNLP2FPNLP &) | |
Copy Constructor. | |
void | operator= (const TNLP2FPNLP &) |
Overloaded Equals Operator. | |
Private Attributes | |
SmartPtr< TNLP > | tnlp_ |
pointer to the tminlp that is being adapted | |
double | objectiveScalingFactor_ |
Scaling factor for the objective. | |
Data for storing the point the distance to which is minimized | |
Index | n_ |
Number of variables in inds_ and vals_. | |
Index | nMax_ |
Size of inds_ and vals_ arrays. | |
Index * | inds_ |
Indices of the variables for which distance is minimized (i.e. indices of integer variables in a feasibility pump setting). | |
Number * | vals_ |
Values of the point to which we separate (if x is the point vals_[i] should be x[inds_[i]] ). |
The extra function is set_dist2point_obj(int n, const double *, const int *)
Definition at line 21 of file TNLP2FPNLP.hpp.
virtual Ipopt::TNLP2FPNLP::~TNLP2FPNLP | ( | ) | [virtual] |
Default destructor.
Ipopt::TNLP2FPNLP::TNLP2FPNLP | ( | ) | [private] |
Default Constructor.
Ipopt::TNLP2FPNLP::TNLP2FPNLP | ( | const TNLP2FPNLP & | ) | [private] |
Copy Constructor.
Set the point to which distance is minimized.
The distance is minimize in a subspace define by a subset of coordinates
n | number of coordinates on which distance is minimized | |
inds | indices of the coordinates on which distance is minimized | |
vals | values of the point for coordinates in ind |
virtual bool Ipopt::TNLP2FPNLP::get_nlp_info | ( | Index & | n, | |
Index & | m, | |||
Index & | nnz_jac_g, | |||
Index & | nnz_h_lag, | |||
TNLP::IndexStyleEnum & | index_style | |||
) | [virtual] |
virtual bool Ipopt::TNLP2FPNLP::get_bounds_info | ( | Index | n, | |
Number * | x_l, | |||
Number * | x_u, | |||
Index | m, | |||
Number * | g_l, | |||
Number * | g_u | |||
) | [inline, virtual] |
This call is just passed onto tnlp_.
Implements Ipopt::TNLP.
Definition at line 51 of file TNLP2FPNLP.hpp.
References tnlp_.
virtual bool Ipopt::TNLP2FPNLP::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 | |||
) | [inline, virtual] |
Passed onto tnlp_.
Implements Ipopt::TNLP.
Definition at line 59 of file TNLP2FPNLP.hpp.
References tnlp_.
virtual bool Ipopt::TNLP2FPNLP::eval_grad_f | ( | Index | n, | |
const Number * | x, | |||
bool | new_x, | |||
Number * | grad_f | |||
) | [virtual] |
overload this method to return the vector of the gradient of the objective w.r.t.
x
Implements Ipopt::TNLP.
virtual bool Ipopt::TNLP2FPNLP::eval_g | ( | Index | n, | |
const Number * | x, | |||
bool | new_x, | |||
Index | m, | |||
Number * | g | |||
) | [inline, virtual] |
passed onto tnlp_
Implements Ipopt::TNLP.
Definition at line 78 of file TNLP2FPNLP.hpp.
References tnlp_.
virtual bool Ipopt::TNLP2FPNLP::eval_jac_g | ( | Index | n, | |
const Number * | x, | |||
bool | new_x, | |||
Index | m, | |||
Index | nele_jac, | |||
Index * | iRow, | |||
Index * | jCol, | |||
Number * | values | |||
) | [inline, virtual] |
Passed onto tnlp_.
Implements Ipopt::TNLP.
Definition at line 85 of file TNLP2FPNLP.hpp.
References tnlp_.
virtual void Ipopt::TNLP2FPNLP::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 | |||
) | [virtual] |
This method is called when the algorithm is complete so the TNLP can store/write the solution.
Implements Ipopt::TNLP.
void Ipopt::TNLP2FPNLP::setObjectiveScaling | ( | double | value | ) | [inline] |
double Ipopt::TNLP2FPNLP::getObjectiveScaling | ( | ) | const [inline] |
double Ipopt::TNLP2FPNLP::dist2point | ( | const Number * | x | ) | [private] |
Compute the norm-2 distance to the current point to which distance is minimized.
void Ipopt::TNLP2FPNLP::operator= | ( | const TNLP2FPNLP & | ) | [private] |
Overloaded Equals Operator.
SmartPtr<TNLP> Ipopt::TNLP2FPNLP::tnlp_ [private] |
pointer to the tminlp that is being adapted
Definition at line 144 of file TNLP2FPNLP.hpp.
Referenced by eval_g(), eval_jac_g(), get_bounds_info(), and get_starting_point().
Index Ipopt::TNLP2FPNLP::n_ [private] |
Index Ipopt::TNLP2FPNLP::nMax_ [private] |
Index* Ipopt::TNLP2FPNLP::inds_ [private] |
Indices of the variables for which distance is minimized (i.e. indices of integer variables in a feasibility pump setting).
Definition at line 153 of file TNLP2FPNLP.hpp.
Number* Ipopt::TNLP2FPNLP::vals_ [private] |
Values of the point to which we separate (if x is the point vals_[i] should be x[inds_[i]] ).
Definition at line 155 of file TNLP2FPNLP.hpp.
double Ipopt::TNLP2FPNLP::objectiveScalingFactor_ [private] |
Scaling factor for the objective.
Definition at line 159 of file TNLP2FPNLP.hpp.
Referenced by getObjectiveScaling(), and setObjectiveScaling().