Ipopt
3.12.12
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This is the abstract base class for classes that map the traditional NLP into something that is more useful by Ipopt. More...
#include <IpIpoptNLP.hpp>
Public Member Functions | |
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)=0 |
Initialize (create) structures for the iteration data. More... | |
virtual bool | GetWarmStartIterate (IteratesVector &warm_start_iterate)=0 |
Method accessing the GetWarmStartIterate of the NLP. 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)=0 |
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)=0 |
Method for adapting the variable bounds. More... | |
SmartPtr< NLPScalingObject > | NLP_scaling () const |
Returns the scaling strategy object. More... | |
Constructors/Destructors | |
IpoptNLP (const SmartPtr< NLPScalingObject > nlp_scaling) | |
virtual | ~IpoptNLP () |
Default destructor. More... | |
Possible Exceptions | |
DECLARE_STD_EXCEPTION (Eval_Error) | |
thrown if there is any error evaluating values from the nlp More... | |
virtual Number | f (const Vector &x)=0 |
Accessor methods for model data. More... | |
virtual SmartPtr< const Vector > | grad_f (const Vector &x)=0 |
Gradient of the objective. More... | |
virtual SmartPtr< const Vector > | c (const Vector &x)=0 |
Equality constraint residual. More... | |
virtual SmartPtr< const Matrix > | jac_c (const Vector &x)=0 |
Jacobian Matrix for equality constraints. More... | |
virtual SmartPtr< const Vector > | d (const Vector &x)=0 |
Inequality constraint residual (reformulated as equalities with slacks. More... | |
virtual SmartPtr< const Matrix > | jac_d (const Vector &x)=0 |
Jacobian Matrix for inequality constraints. More... | |
virtual SmartPtr< const SymMatrix > | h (const Vector &x, Number obj_factor, const Vector &yc, const Vector &yd)=0 |
Hessian of the Lagrangian. More... | |
virtual SmartPtr< const Vector > | x_L () const =0 |
Lower bounds on x. More... | |
virtual SmartPtr< const Matrix > | Px_L () const =0 |
Permutation matrix (x_L_ -> x) More... | |
virtual SmartPtr< const Vector > | x_U () const =0 |
Upper bounds on x. More... | |
virtual SmartPtr< const Matrix > | Px_U () const =0 |
Permutation matrix (x_U_ -> x. More... | |
virtual SmartPtr< const Vector > | d_L () const =0 |
Lower bounds on d. More... | |
virtual SmartPtr< const Matrix > | Pd_L () const =0 |
Permutation matrix (d_L_ -> d) More... | |
virtual SmartPtr< const Vector > | d_U () const =0 |
Upper bounds on d. More... | |
virtual SmartPtr< const Matrix > | Pd_U () const =0 |
Permutation matrix (d_U_ -> d. More... | |
virtual SmartPtr< const VectorSpace > | x_space () const =0 |
x_space More... | |
virtual SmartPtr< const SymMatrixSpace > | HessianMatrixSpace () const =0 |
Accessor method to obtain the MatrixSpace for the Hessian matrix (or it's approximation) More... | |
Counters for the number of function evaluations. | |
virtual Index | f_evals () const =0 |
virtual Index | grad_f_evals () const =0 |
virtual Index | c_evals () const =0 |
virtual Index | jac_c_evals () const =0 |
virtual Index | d_evals () const =0 |
virtual Index | jac_d_evals () const =0 |
virtual Index | h_evals () const =0 |
Special method for dealing with the fact that the | |
restoration phase objective function depends on the barrier parameter | |
virtual bool | objective_depends_on_mu () const |
Method for telling the IpoptCalculatedQuantities class whether the objective function depends on the barrier function. More... | |
virtual Number | f (const Vector &x, Number mu)=0 |
Replacement for the default objective function method which knows about the barrier parameter. More... | |
virtual SmartPtr< const Vector > | grad_f (const Vector &x, Number mu)=0 |
Replacement for the default objective gradient method which knows about the barrier parameter. More... | |
virtual SmartPtr< const SymMatrix > | h (const Vector &x, Number obj_factor, const Vector &yc, const Vector &yd, Number mu)=0 |
Replacement for the default Lagrangian Hessian method which knows about the barrier parameter. More... | |
virtual SmartPtr< const SymMatrix > | uninitialized_h ()=0 |
Provides a Hessian matrix from the correct matrix space with uninitialized values. More... | |
solution routines | |
virtual void | FinalizeSolution (SolverReturn status, const Vector &x, const Vector &z_L, const Vector &z_U, const Vector &c, const Vector &d, const Vector &y_c, const Vector &y_d, Number obj_value, const IpoptData *ip_data, IpoptCalculatedQuantities *ip_cq)=0 |
virtual 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)=0 |
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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. | |
IpoptNLP (const IpoptNLP &) | |
Copy Constructor. More... | |
void | operator= (const IpoptNLP &) |
Overloaded Equals Operator. More... | |
Private Attributes | |
SmartPtr< NLPScalingObject > | nlp_scaling_ |
This is the abstract base class for classes that map the traditional NLP into something that is more useful by Ipopt.
This class takes care of storing the calculated model results, handles cacheing, and (some day) takes care of addition of slacks.
Definition at line 28 of file IpIpoptNLP.hpp.
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inline |
Definition at line 33 of file IpIpoptNLP.hpp.
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inlinevirtual |
Default destructor.
Definition at line 39 of file IpIpoptNLP.hpp.
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private |
Copy Constructor.
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inlinevirtual |
Initialization method.
Set the internal options and initialize internal data structures.
Reimplemented in Ipopt::OrigIpoptNLP, and Ipopt::RestoIpoptNLP.
Definition at line 45 of file IpIpoptNLP.hpp.
Ipopt::IpoptNLP::DECLARE_STD_EXCEPTION | ( | Eval_Error | ) |
thrown if there is any error evaluating values from the nlp
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pure virtual |
Initialize (create) structures for the iteration data.
Implemented in Ipopt::OrigIpoptNLP, and Ipopt::RestoIpoptNLP.
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pure virtual |
Method accessing the GetWarmStartIterate of the NLP.
Implemented in Ipopt::OrigIpoptNLP, and Ipopt::RestoIpoptNLP.
Accessor methods for model data.
Objective value
Implemented in Ipopt::RestoIpoptNLP, and Ipopt::OrigIpoptNLP.
Gradient of the objective.
Implemented in Ipopt::RestoIpoptNLP, and Ipopt::OrigIpoptNLP.
Equality constraint residual.
Implemented in Ipopt::RestoIpoptNLP, and Ipopt::OrigIpoptNLP.
Jacobian Matrix for equality constraints.
Implemented in Ipopt::RestoIpoptNLP, and Ipopt::OrigIpoptNLP.
Inequality constraint residual (reformulated as equalities with slacks.
Implemented in Ipopt::RestoIpoptNLP, and Ipopt::OrigIpoptNLP.
Jacobian Matrix for inequality constraints.
Implemented in Ipopt::RestoIpoptNLP, and Ipopt::OrigIpoptNLP.
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pure virtual |
Hessian of the Lagrangian.
Implemented in Ipopt::RestoIpoptNLP, and Ipopt::OrigIpoptNLP.
Lower bounds on x.
Implemented in Ipopt::RestoIpoptNLP, and Ipopt::OrigIpoptNLP.
Permutation matrix (x_L_ -> x)
Implemented in Ipopt::RestoIpoptNLP, and Ipopt::OrigIpoptNLP.
Upper bounds on x.
Implemented in Ipopt::RestoIpoptNLP, and Ipopt::OrigIpoptNLP.
Permutation matrix (x_U_ -> x.
Implemented in Ipopt::RestoIpoptNLP, and Ipopt::OrigIpoptNLP.
Lower bounds on d.
Implemented in Ipopt::RestoIpoptNLP, and Ipopt::OrigIpoptNLP.
Permutation matrix (d_L_ -> d)
Implemented in Ipopt::RestoIpoptNLP, and Ipopt::OrigIpoptNLP.
Upper bounds on d.
Implemented in Ipopt::RestoIpoptNLP, and Ipopt::OrigIpoptNLP.
Permutation matrix (d_U_ -> d.
Implemented in Ipopt::RestoIpoptNLP, and Ipopt::OrigIpoptNLP.
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pure virtual |
x_space
Implemented in Ipopt::RestoIpoptNLP, and Ipopt::OrigIpoptNLP.
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pure virtual |
Accessor method to obtain the MatrixSpace for the Hessian matrix (or it's approximation)
Implemented in Ipopt::RestoIpoptNLP, and Ipopt::OrigIpoptNLP.
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pure virtual |
Accessor method for vector/matrix spaces pointers.
Implemented in Ipopt::RestoIpoptNLP, and Ipopt::OrigIpoptNLP.
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pure virtual |
Method for adapting the variable bounds.
This is called if slacks are becoming too small
Implemented in Ipopt::RestoIpoptNLP, and Ipopt::OrigIpoptNLP.
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pure virtual |
Implemented in Ipopt::RestoIpoptNLP, and Ipopt::OrigIpoptNLP.
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pure virtual |
Implemented in Ipopt::RestoIpoptNLP, and Ipopt::OrigIpoptNLP.
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pure virtual |
Implemented in Ipopt::RestoIpoptNLP, and Ipopt::OrigIpoptNLP.
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pure virtual |
Implemented in Ipopt::RestoIpoptNLP, and Ipopt::OrigIpoptNLP.
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pure virtual |
Implemented in Ipopt::RestoIpoptNLP, and Ipopt::OrigIpoptNLP.
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pure virtual |
Implemented in Ipopt::RestoIpoptNLP, and Ipopt::OrigIpoptNLP.
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pure virtual |
Implemented in Ipopt::RestoIpoptNLP, and Ipopt::OrigIpoptNLP.
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inlinevirtual |
Method for telling the IpoptCalculatedQuantities class whether the objective function depends on the barrier function.
This is only used for the restoration phase NLP formulation. Probably only RestoIpoptNLP should overwrite this.
Reimplemented in Ipopt::RestoIpoptNLP.
Definition at line 183 of file IpIpoptNLP.hpp.
Replacement for the default objective function method which knows about the barrier parameter.
Implemented in Ipopt::RestoIpoptNLP, and Ipopt::OrigIpoptNLP.
Replacement for the default objective gradient method which knows about the barrier parameter.
Implemented in Ipopt::RestoIpoptNLP, and Ipopt::OrigIpoptNLP.
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pure virtual |
Replacement for the default Lagrangian Hessian method which knows about the barrier parameter.
Implemented in Ipopt::RestoIpoptNLP, and Ipopt::OrigIpoptNLP.
Provides a Hessian matrix from the correct matrix space with uninitialized values.
This can be used in LeastSquareMults to obtain a "zero Hessian".
Implemented in Ipopt::RestoIpoptNLP, and Ipopt::OrigIpoptNLP.
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pure virtual |
Implemented in Ipopt::OrigIpoptNLP, and Ipopt::RestoIpoptNLP.
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pure virtual |
Implemented in Ipopt::OrigIpoptNLP, and Ipopt::RestoIpoptNLP.
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inline |
Returns the scaling strategy object.
Definition at line 232 of file IpIpoptNLP.hpp.
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private |
Overloaded Equals Operator.
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private |
Definition at line 256 of file IpIpoptNLP.hpp.