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7 #ifndef __IPNLPBOUNDSREMOVER_HPP__
8 #define __IPNLPBOUNDSREMOVER_HPP__
33 bool allow_twosided_inequalities =
false
48 const std::string& prefix
51 return nlp_->ProcessOptions(options, prefix);
113 return nlp_->GetWarmStartIterate(warm_start_iterate);
124 return nlp_->Eval_f(x, f);
132 return nlp_->Eval_grad_f(x, g_f);
140 return nlp_->Eval_c(x, c);
148 return nlp_->Eval_jac_c(x, jac_c);
194 Number regularization_size,
202 return nlp_->IntermediateCallBack(mode, iter, obj_value, inf_pr, inf_du, mu, d_norm, regularization_size,
203 alpha_du, alpha_pr, ls_trials, ip_data, ip_cq);
225 nlp_->GetQuasiNewtonApproximationSpaces(approx_space, P_approx);
virtual bool Eval_jac_c(const Vector &x, Matrix &jac_c)
virtual bool GetBoundsInformation(const Matrix &Px_L, Vector &x_L, const Matrix &Px_U, Vector &x_U, const Matrix &Pd_L, Vector &d_L, const Matrix &Pd_U, Vector &d_U)
Method for obtaining the bounds information.
virtual bool Eval_jac_d(const Vector &x, Matrix &jac_d)
virtual bool Eval_h(const Vector &x, Number obj_factor, const Vector &yc, const Vector &yd, SymMatrix &h)
Class to organize all the data required by the algorithm.
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)
This method is called at the very end of the optimization.
virtual bool Eval_c(const Vector &x, Vector &c)
virtual bool Eval_grad_f(const Vector &x, Vector &g_f)
Class for all IPOPT specific calculated quantities.
This file contains a base class for all exceptions and a set of macros to help with exceptions.
double Number
Type of all numbers.
virtual bool Eval_f(const Vector &x, Number &f)
SmartPtr< const Matrix > Px_l_orig_
Pointer to the expansion matrix for the lower x bounds.
NLPBoundsRemover()
Default Constructor.
virtual bool ProcessOptions(const OptionsList &options, const std::string &prefix)
Overload if you want the chance to process options or parameters that may be specific to the NLP.
SmartPtr< const VectorSpace > d_space_orig_
Pointer to the original d space.
bool allow_twosided_inequalities_
Flag indicating whether twosided inequality constraints are allowed.
virtual ~NLPBoundsRemover()
Destructor.
int Index
Type of all indices of vectors, matrices etc.
virtual void GetScalingParameters(const SmartPtr< const VectorSpace > x_space, const SmartPtr< const VectorSpace > c_space, const SmartPtr< const VectorSpace > d_space, Number &obj_scaling, SmartPtr< Vector > &x_scaling, SmartPtr< Vector > &c_scaling, SmartPtr< Vector > &d_scaling) const
Routines to get the scaling parameters.
This is an adapter for an NLP that converts variable bound constraints to inequality constraints.
SmartPtr< NLP > nlp()
Accessor method to the original NLP.
Template class for Smart Pointers.
virtual bool GetStartingPoint(SmartPtr< Vector > x, bool need_x, SmartPtr< Vector > y_c, bool need_y_c, SmartPtr< Vector > y_d, bool need_y_d, SmartPtr< Vector > z_L, bool need_z_L, SmartPtr< Vector > z_U, bool need_z_U)
Method for obtaining the starting point for all the iterates.
SmartPtr< const Matrix > Px_u_orig_
Pointer to the expansion matrix for the upper x bounds.
virtual bool GetWarmStartIterate(IteratesVector &warm_start_iterate)
Method for obtaining an entire iterate as a warmstart point.
virtual bool Eval_d(const Vector &x, Vector &d)
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, const IpoptData *ip_data, IpoptCalculatedQuantities *ip_cq)
This method is called once per iteration, after the iteration summary output has been printed.
SmartPtr< NLP > nlp_
Pointer to the original NLP.
This is the base class for all derived symmetric matrix types.
virtual bool 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)
Method for creating the derived vector / matrix types.
virtual void GetQuasiNewtonApproximationSpaces(SmartPtr< VectorSpace > &approx_space, SmartPtr< Matrix > &P_approx)
Method for obtaining the subspace in which the limited-memory Hessian approximation should be done.
SolverReturn
enum for the return from the optimize algorithm
This class stores a list of user set options.
void operator=(const NLPBoundsRemover &)
Default Assignment Operator.
AlgorithmMode
enum to indicate the mode in which the algorithm is
Specialized CompoundVector class specifically for the algorithm iterates.