This class maps the traditional NLP into something that is more useful by Ipopt. More...
#include <IpRestoIpoptNLP.hpp>
Public Member Functions | |
Constructors/Destructors | |
RestoIpoptNLP (IpoptNLP &orig_ip_nlp, IpoptData &orig_ip_data, IpoptCalculatedQuantities &orig_ip_cq) | |
~RestoIpoptNLP () | |
Destructor. More... | |
virtual bool | Initialize (const Journalist &jnlst, const OptionsList &options, const std::string &prefix) |
Initialization method. More... | |
virtual bool | InitializeStructures (SmartPtr< Vector > &x, bool init_x, SmartPtr< Vector > &y_c, bool init_y_c, SmartPtr< Vector > &y_d, bool init_y_d, SmartPtr< Vector > &z_L, bool init_z_L, SmartPtr< Vector > &z_U, bool init_z_U, SmartPtr< Vector > &v_L, SmartPtr< Vector > &v_U) |
Initialize (create) structures for the iteration data. More... | |
virtual bool | GetWarmStartIterate (IteratesVector &) |
Method accessing the GetWarmStartIterate of the NLP. More... | |
void | FinalizeSolution (SolverReturn, const Vector &, const Vector &, const Vector &, const Vector &, const Vector &, const Vector &, const Vector &, Number, const IpoptData *, IpoptCalculatedQuantities *) |
virtual bool | objective_depends_on_mu () const |
Accessor methods for model data. More... | |
virtual Number | f (const Vector &x) |
Objective value (incorrect version for restoration phase) More... | |
virtual Number | f (const Vector &x, Number mu) |
Objective value. More... | |
virtual SmartPtr< const Vector > | grad_f (const Vector &x) |
Gradient of the objective (incorrect version for restoration phase) More... | |
virtual SmartPtr< const Vector > | grad_f (const Vector &x, Number mu) |
Gradient of the objective. More... | |
virtual SmartPtr< const Vector > | c (const Vector &x) |
Equality constraint residual. More... | |
virtual SmartPtr< const Matrix > | jac_c (const Vector &x) |
Jacobian Matrix for equality constraints. More... | |
virtual SmartPtr< const Vector > | d (const Vector &x) |
Inequality constraint residual (reformulated as equalities with slacks. More... | |
virtual SmartPtr< const Matrix > | jac_d (const Vector &x) |
Jacobian Matrix for inequality constraints. More... | |
virtual SmartPtr< const SymMatrix > | h (const Vector &x, Number obj_factor, const Vector &yc, const Vector &yd) |
Hessian of the Lagrangian (incorrect version for restoration phase) More... | |
virtual SmartPtr< const SymMatrix > | h (const Vector &x, Number obj_factor, const Vector &yc, const Vector &yd, Number mu) |
Hessian of the Lagrangian. More... | |
virtual SmartPtr< const SymMatrix > | uninitialized_h () |
Provides a Hessian matrix from the correct matrix space with uninitialized values. More... | |
virtual SmartPtr< const Vector > | x_L () const |
Lower bounds on x. More... | |
virtual SmartPtr< const Matrix > | Px_L () const |
Permutation matrix (x_L_ -> x) More... | |
virtual SmartPtr< const Vector > | x_U () const |
Upper bounds on x. More... | |
virtual SmartPtr< const Matrix > | Px_U () const |
Permutation matrix (x_U_ -> x. More... | |
virtual SmartPtr< const Vector > | d_L () const |
Lower bounds on d. More... | |
virtual SmartPtr< const Matrix > | Pd_L () const |
Permutation matrix (d_L_ -> d) More... | |
virtual SmartPtr< const Vector > | d_U () const |
Upper bounds on d. More... | |
virtual SmartPtr< const Matrix > | Pd_U () const |
Permutation matrix (d_U_ -> d. More... | |
virtual SmartPtr< const SymMatrixSpace > | HessianMatrixSpace () const |
Accessor method to obtain the MatrixSpace for the Hessian matrix (or it's approximation) More... | |
virtual SmartPtr< const VectorSpace > | x_space () const |
x_space More... | |
virtual void | GetSpaces (SmartPtr< const VectorSpace > &x_space, SmartPtr< const VectorSpace > &c_space, SmartPtr< const VectorSpace > &d_space, SmartPtr< const VectorSpace > &x_l_space, SmartPtr< const MatrixSpace > &px_l_space, SmartPtr< const VectorSpace > &x_u_space, SmartPtr< const MatrixSpace > &px_u_space, SmartPtr< const VectorSpace > &d_l_space, SmartPtr< const MatrixSpace > &pd_l_space, SmartPtr< const VectorSpace > &d_u_space, SmartPtr< const MatrixSpace > &pd_u_space, SmartPtr< const MatrixSpace > &Jac_c_space, SmartPtr< const MatrixSpace > &Jac_d_space, SmartPtr< const SymMatrixSpace > &Hess_lagrangian_space) |
Accessor method for vector/matrix spaces pointers. More... | |
virtual void | AdjustVariableBounds (const Vector &new_x_L, const Vector &new_x_U, const Vector &new_d_L, const Vector &new_d_U) |
Method for adapting the variable bounds. More... | |
bool | IntermediateCallBack (AlgorithmMode mode, Index iter, Number obj_value, Number inf_pr, Number inf_du, Number mu, Number d_norm, Number regularization_size, Number alpha_du, Number alpha_pr, Index ls_trials, SmartPtr< const IpoptData > ip_data, SmartPtr< IpoptCalculatedQuantities > ip_cq) |
User callback method. More... | |
Accessor method for the information of the original NLP. | |
These methods are not overloaded from IpoptNLP. | |
IpoptNLP & | OrigIpNLP () const |
IpoptData & | OrigIpData () const |
IpoptCalculatedQuantities & | OrigIpCq () const |
Number | Rho () const |
Accessor Method for obtaining the Rho penalization factor for the ell_1 norm. More... | |
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IpoptNLP (const SmartPtr< NLPScalingObject > nlp_scaling) | |
virtual | ~IpoptNLP () |
Destructor. More... | |
DECLARE_STD_EXCEPTION (Eval_Error) | |
thrown if there is any error evaluating values from the nlp More... | |
SmartPtr< NLPScalingObject > | NLP_scaling () const |
Returns the scaling strategy object. More... | |
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ReferencedObject () | |
virtual | ~ReferencedObject () |
Index | ReferenceCount () const |
void | AddRef (const Referencer *referencer) const |
void | ReleaseRef (const Referencer *referencer) const |
Private Member Functions | |
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. | |
RestoIpoptNLP () | |
Default Constructor. More... | |
RestoIpoptNLP (const RestoIpoptNLP &) | |
Copy Constructor. More... | |
void | operator= (const RestoIpoptNLP &) |
Default Assignment Operator. More... | |
Counters for the number of function evaluations. | |
virtual Index | f_evals () const |
virtual Index | grad_f_evals () const |
virtual Index | c_evals () const |
virtual Index | jac_c_evals () const |
virtual Index | d_evals () const |
virtual Index | jac_d_evals () const |
virtual Index | h_evals () const |
Number | Eta (Number mu) const |
Method to calculate eta, the factor for the regularization term. More... | |
SmartPtr< const Vector > | DR_x () const |
Method returning the scaling factors for the 2-norm penalization term. More... | |
static void | RegisterOptions (SmartPtr< RegisteredOptions > roptions) |
This class maps the traditional NLP into something that is more useful by Ipopt.
This class takes care of storing the calculated model results, handles caching, and (some day) takes care of addition of slacks.
Definition at line 31 of file IpRestoIpoptNLP.hpp.
Ipopt::RestoIpoptNLP::RestoIpoptNLP | ( | IpoptNLP & | orig_ip_nlp, |
IpoptData & | orig_ip_data, | ||
IpoptCalculatedQuantities & | orig_ip_cq | ||
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Ipopt::RestoIpoptNLP::~RestoIpoptNLP | ( | ) |
Destructor.
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Default Constructor.
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Copy Constructor.
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Initialization method.
Set the internal options and initialize internal data structures.
Reimplemented from Ipopt::IpoptNLP.
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Initialize (create) structures for the iteration data.
Implements Ipopt::IpoptNLP.
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Method accessing the GetWarmStartIterate of the NLP.
Implements Ipopt::IpoptNLP.
Definition at line 68 of file IpRestoIpoptNLP.hpp.
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Implements Ipopt::IpoptNLP.
Definition at line 75 of file IpRestoIpoptNLP.hpp.
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Accessor methods for model data.
Method for telling IpoptCalculatedQuantities that the restoration phase objective function depends on the barrier parameter
Reimplemented from Ipopt::IpoptNLP.
Definition at line 96 of file IpRestoIpoptNLP.hpp.
Objective value (incorrect version for restoration phase)
Implements Ipopt::IpoptNLP.
Objective value.
Implements Ipopt::IpoptNLP.
Gradient of the objective (incorrect version for restoration phase)
Implements Ipopt::IpoptNLP.
Gradient of the objective.
Implements Ipopt::IpoptNLP.
Equality constraint residual.
Implements Ipopt::IpoptNLP.
Jacobian Matrix for equality constraints.
Implements Ipopt::IpoptNLP.
Inequality constraint residual (reformulated as equalities with slacks.
Implements Ipopt::IpoptNLP.
Jacobian Matrix for inequality constraints.
Implements Ipopt::IpoptNLP.
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Hessian of the Lagrangian (incorrect version for restoration phase)
Implements Ipopt::IpoptNLP.
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Hessian of the Lagrangian.
Implements Ipopt::IpoptNLP.
Provides a Hessian matrix from the correct matrix space with uninitialized values.
This can be used in LeastSquareMults to obtain a "zero Hessian".
Implements Ipopt::IpoptNLP.
Permutation matrix (x_L_ -> x)
Implements Ipopt::IpoptNLP.
Definition at line 175 of file IpRestoIpoptNLP.hpp.
Permutation matrix (x_U_ -> x.
Implements Ipopt::IpoptNLP.
Definition at line 187 of file IpRestoIpoptNLP.hpp.
Permutation matrix (d_L_ -> d)
Implements Ipopt::IpoptNLP.
Definition at line 199 of file IpRestoIpoptNLP.hpp.
Permutation matrix (d_U_ -> d.
Implements Ipopt::IpoptNLP.
Definition at line 211 of file IpRestoIpoptNLP.hpp.
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Accessor method to obtain the MatrixSpace for the Hessian matrix (or it's approximation)
Implements Ipopt::IpoptNLP.
Definition at line 216 of file IpRestoIpoptNLP.hpp.
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Accessor method for vector/matrix spaces pointers.
Implements Ipopt::IpoptNLP.
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Method for adapting the variable bounds.
This is called if slacks are becoming too small.
Implements Ipopt::IpoptNLP.
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User callback method.
Implements Ipopt::IpoptNLP.
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Definition at line 276 of file IpRestoIpoptNLP.hpp.
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Definition at line 281 of file IpRestoIpoptNLP.hpp.
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Definition at line 286 of file IpRestoIpoptNLP.hpp.
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Accessor Method for obtaining the Rho penalization factor for the ell_1 norm.
Definition at line 295 of file IpRestoIpoptNLP.hpp.
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Implements Ipopt::IpoptNLP.
Definition at line 302 of file IpRestoIpoptNLP.hpp.
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Implements Ipopt::IpoptNLP.
Definition at line 306 of file IpRestoIpoptNLP.hpp.
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Implements Ipopt::IpoptNLP.
Definition at line 310 of file IpRestoIpoptNLP.hpp.
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Implements Ipopt::IpoptNLP.
Definition at line 314 of file IpRestoIpoptNLP.hpp.
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Implements Ipopt::IpoptNLP.
Definition at line 318 of file IpRestoIpoptNLP.hpp.
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Implements Ipopt::IpoptNLP.
Definition at line 322 of file IpRestoIpoptNLP.hpp.
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Implements Ipopt::IpoptNLP.
Definition at line 326 of file IpRestoIpoptNLP.hpp.
Method to calculate eta, the factor for the regularization term.
Method returning the scaling factors for the 2-norm penalization term.
Definition at line 340 of file IpRestoIpoptNLP.hpp.
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Default Assignment Operator.
Pointer to the original IpoptNLP.
Definition at line 353 of file IpRestoIpoptNLP.hpp.
Pointer to the original IpoptData.
Definition at line 356 of file IpRestoIpoptNLP.hpp.
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Pointer to the original IpoptCalculatedQuantities.
Definition at line 359 of file IpRestoIpoptNLP.hpp.
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Necessary Vector/Matrix spaces.
Definition at line 364 of file IpRestoIpoptNLP.hpp.
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Definition at line 366 of file IpRestoIpoptNLP.hpp.
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Definition at line 368 of file IpRestoIpoptNLP.hpp.
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Definition at line 370 of file IpRestoIpoptNLP.hpp.
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Definition at line 372 of file IpRestoIpoptNLP.hpp.
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Definition at line 374 of file IpRestoIpoptNLP.hpp.
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Definition at line 376 of file IpRestoIpoptNLP.hpp.
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Definition at line 378 of file IpRestoIpoptNLP.hpp.
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Definition at line 380 of file IpRestoIpoptNLP.hpp.
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Definition at line 382 of file IpRestoIpoptNLP.hpp.
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Definition at line 384 of file IpRestoIpoptNLP.hpp.
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Definition at line 386 of file IpRestoIpoptNLP.hpp.
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Definition at line 388 of file IpRestoIpoptNLP.hpp.
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Definition at line 390 of file IpRestoIpoptNLP.hpp.
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Lower bounds on x.
Definition at line 396 of file IpRestoIpoptNLP.hpp.
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Permutation matrix (x_L_ -> x)
Definition at line 399 of file IpRestoIpoptNLP.hpp.
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Upper bounds on x.
Definition at line 402 of file IpRestoIpoptNLP.hpp.
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Permutation matrix (x_U_ -> x)
Definition at line 405 of file IpRestoIpoptNLP.hpp.
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Lower bounds on d.
Definition at line 408 of file IpRestoIpoptNLP.hpp.
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Permutation matrix (d_L_ -> d)
Definition at line 411 of file IpRestoIpoptNLP.hpp.
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Upper bounds on d.
Definition at line 414 of file IpRestoIpoptNLP.hpp.
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Permutation matrix (d_U_ -> d.
Definition at line 417 of file IpRestoIpoptNLP.hpp.
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Penalty parameter for the $l_1$ norm.
Definition at line 425 of file IpRestoIpoptNLP.hpp.
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scaling factor for eta calculation
Definition at line 428 of file IpRestoIpoptNLP.hpp.
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exponent for mu in eta calculation
Definition at line 431 of file IpRestoIpoptNLP.hpp.
Scaling factors for the $x$ part of the regularization term.
Definition at line 436 of file IpRestoIpoptNLP.hpp.
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Definition at line 437 of file IpRestoIpoptNLP.hpp.
$x$ part of the reference point in the regularization term
Definition at line 440 of file IpRestoIpoptNLP.hpp.
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Flag indicating if evaluation of the objective should be performed for every restoration phase objective function evaluation.
Definition at line 472 of file IpRestoIpoptNLP.hpp.
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Flag indicating how Hessian information is obtained.
Definition at line 475 of file IpRestoIpoptNLP.hpp.
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Flag indicating if initialization method has been called.
Definition at line 479 of file IpRestoIpoptNLP.hpp.
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Definition at line 483 of file IpRestoIpoptNLP.hpp.
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Definition at line 484 of file IpRestoIpoptNLP.hpp.
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Definition at line 485 of file IpRestoIpoptNLP.hpp.
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Definition at line 486 of file IpRestoIpoptNLP.hpp.
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Definition at line 487 of file IpRestoIpoptNLP.hpp.
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Definition at line 488 of file IpRestoIpoptNLP.hpp.
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Definition at line 489 of file IpRestoIpoptNLP.hpp.