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IpNLPBoundsRemover.hpp
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1 // Copyright (C) 2008, 2010 International Business Machines and others.
2 // All Rights Reserved.
3 // This code is published under the Eclipse Public License.
4 //
5 // $Id: IpNLP.hpp 949 2007-03-27 00:41:26Z andreasw $
6 //
7 // Authors: Andreas Waechter IBM 2008-08-25
8
9 #ifndef __IPNLPBOUNDSREMOVER_HPP__
10 #define __IPNLPBOUNDSREMOVER_HPP__
11
12 #include "IpNLP.hpp"
13
14 namespace Ipopt
15 {
24 class NLPBoundsRemover : public NLP
25 {
26 public:
31 NLPBoundsRemover(NLP& nlp, bool allow_twosided_inequalities = false);
32
34 virtual ~NLPBoundsRemover()
35 {}
37
43 virtual bool ProcessOptions(const OptionsList& options,
44 const std::string& prefix)
45 {
46 return nlp_->ProcessOptions(options, prefix);
47 }
48
52 virtual bool GetSpaces(SmartPtr<const VectorSpace>& x_space,
53 SmartPtr<const VectorSpace>& c_space,
54 SmartPtr<const VectorSpace>& d_space,
55 SmartPtr<const VectorSpace>& x_l_space,
56 SmartPtr<const MatrixSpace>& px_l_space,
57 SmartPtr<const VectorSpace>& x_u_space,
58 SmartPtr<const MatrixSpace>& px_u_space,
59 SmartPtr<const VectorSpace>& d_l_space,
60 SmartPtr<const MatrixSpace>& pd_l_space,
61 SmartPtr<const VectorSpace>& d_u_space,
62 SmartPtr<const MatrixSpace>& pd_u_space,
63 SmartPtr<const MatrixSpace>& Jac_c_space,
64 SmartPtr<const MatrixSpace>& Jac_d_space,
65 SmartPtr<const SymMatrixSpace>& Hess_lagrangian_space);
66
68 virtual bool GetBoundsInformation(const Matrix& Px_L,
69 Vector& x_L,
70 const Matrix& Px_U,
71 Vector& x_U,
72 const Matrix& Pd_L,
73 Vector& d_L,
74 const Matrix& Pd_U,
75 Vector& d_U);
76
80 virtual bool GetStartingPoint(SmartPtr<Vector> x,
81 bool need_x,
82 SmartPtr<Vector> y_c,
83 bool need_y_c,
84 SmartPtr<Vector> y_d,
85 bool need_y_d,
86 SmartPtr<Vector> z_L,
87 bool need_z_L,
88 SmartPtr<Vector> z_U,
89 bool need_z_U);
90
94 virtual bool GetWarmStartIterate(IteratesVector& warm_start_iterate)
95 {
96 return nlp_->GetWarmStartIterate(warm_start_iterate);
97 }
99
103 virtual bool Eval_f(const Vector& x, Number& f)
104 {
105 return nlp_->Eval_f(x, f);
106 }
107
108 virtual bool Eval_grad_f(const Vector& x, Vector& g_f)
109 {
110 return nlp_->Eval_grad_f(x, g_f);
111 }
112
113 virtual bool Eval_c(const Vector& x, Vector& c)
114 {
115 return nlp_->Eval_c(x, c);
116 }
117
118 virtual bool Eval_jac_c(const Vector& x, Matrix& jac_c)
119 {
120 return nlp_->Eval_jac_c(x, jac_c);
121 }
122
123 virtual bool Eval_d(const Vector& x, Vector& d);
124
125 virtual bool Eval_jac_d(const Vector& x, Matrix& jac_d);
126
127 virtual bool Eval_h(const Vector& x,
128 Number obj_factor,
129 const Vector& yc,
130 const Vector& yd,
131 SymMatrix& h);
133
142 virtual void FinalizeSolution(SolverReturn status,
143 const Vector& x, const Vector& z_L,
144 const Vector& z_U,
145 const Vector& c, const Vector& d,
146 const Vector& y_c, const Vector& y_d,
147 Number obj_value,
148 const IpoptData* ip_data,
149 IpoptCalculatedQuantities* ip_cq);
150
166 virtual bool IntermediateCallBack(AlgorithmMode mode,
167 Index iter, Number obj_value,
168 Number inf_pr, Number inf_du,
169 Number mu, Number d_norm,
170 Number regularization_size,
171 Number alpha_du, Number alpha_pr,
172 Index ls_trials,
173 const IpoptData* ip_data,
174 IpoptCalculatedQuantities* ip_cq)
175 {
176 return nlp_->IntermediateCallBack(mode,iter, obj_value, inf_pr, inf_du,
177 mu, d_norm, regularization_size,
178 alpha_du, alpha_pr, ls_trials,
179 ip_data, ip_cq);
180 }
182
187 virtual void GetScalingParameters(
188 const SmartPtr<const VectorSpace> x_space,
189 const SmartPtr<const VectorSpace> c_space,
190 const SmartPtr<const VectorSpace> d_space,
191 Number& obj_scaling,
192 SmartPtr<Vector>& x_scaling,
193 SmartPtr<Vector>& c_scaling,
194 SmartPtr<Vector>& d_scaling) const;
196
210 virtual void
211 GetQuasiNewtonApproximationSpaces(SmartPtr<VectorSpace>& approx_space,
212 SmartPtr<Matrix>& P_approx)
213 {
214 nlp_->GetQuasiNewtonApproximationSpaces(approx_space, P_approx);
215 }
216
218 SmartPtr<NLP> nlp()
219 {
220 return nlp_;
221 }
222
223 private:
233 NLPBoundsRemover();
235 NLPBoundsRemover(const NLPBoundsRemover&);
236
238 void operator=(const NLPBoundsRemover&);
240
242 SmartPtr<NLP> nlp_;
243
245 SmartPtr<const Matrix> Px_l_orig_;
246
248 SmartPtr<const Matrix> Px_u_orig_;
249
251 SmartPtr<const VectorSpace> d_space_orig_;
252
255 bool allow_twosided_inequalities_;
256 };
257
258 } // namespace Ipopt
259
260 #endif
x
Number * x
Input: Starting point Output: Optimal solution.
Definition: IpStdCInterface.h:238
Ipopt::NLPBoundsRemover::~NLPBoundsRemover
virtual ~NLPBoundsRemover()
Default destructor.
Definition: IpNLPBoundsRemover.hpp:34
Ipopt::IteratesVector
Specialized CompoundVector class specifically for the algorithm iterates.
Definition: IpIteratesVector.hpp:27
Ipopt::IpoptCalculatedQuantities
Class for all IPOPT specific calculated quantities.
Definition: IpIpoptCalculatedQuantities.hpp:81
IpNLP.hpp
Ipopt::NLPBoundsRemover::nlp
SmartPtr< NLP > nlp()
Accessor method to the original NLP.
Definition: IpNLPBoundsRemover.hpp:218
Ipopt::NLPBoundsRemover::IntermediateCallBack
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...
Definition: IpNLPBoundsRemover.hpp:166
Ipopt::AlgorithmMode
AlgorithmMode
enum to indicate the mode in which the algorithm is
Definition: IpReturnCodes.hpp:43
Ipopt::Number
double Number
Type of all numbers.
Definition: IpTypes.hpp:17
Ipopt::Vector
Vector Base Class.
Definition: IpVector.hpp:47
Ipopt::NLPBoundsRemover::Eval_jac_c
virtual bool Eval_jac_c(const Vector &x, Matrix &jac_c)
Definition: IpNLPBoundsRemover.hpp:118
Ipopt::NLPBoundsRemover::GetQuasiNewtonApproximationSpaces
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...
Definition: IpNLPBoundsRemover.hpp:211
Ipopt::NLPBoundsRemover::allow_twosided_inequalities_
bool allow_twosided_inequalities_
Flag indicating whether twosided inequality constraints are allowed.
Definition: IpNLPBoundsRemover.hpp:255
Ipopt::NLPBoundsRemover::Eval_jac_d
virtual bool Eval_jac_d(const Vector &x, Matrix &jac_d)
Ipopt::NLPBoundsRemover::Px_u_orig_
SmartPtr< const Matrix > Px_u_orig_
Pointer to the expansion matrix for the upper x bounds.
Definition: IpNLPBoundsRemover.hpp:248
Ipopt::NLPBoundsRemover::Eval_h
virtual bool Eval_h(const Vector &x, Number obj_factor, const Vector &yc, const Vector &yd, SymMatrix &h)
Ipopt::NLPBoundsRemover::Eval_f
virtual bool Eval_f(const Vector &x, Number &f)
Definition: IpNLPBoundsRemover.hpp:103
Ipopt::SymMatrix
This is the base class for all derived symmetric matrix types.
Definition: IpSymMatrix.hpp:23
Ipopt::SmartPtr
Template class for Smart Pointers.
Definition: IpSmartPtr.hpp:172
Ipopt::OptionsList
This class stores a list of user set options.
Definition: IpOptionsList.hpp:32
Ipopt::SolverReturn
SolverReturn
enum for the return from the optimize algorithm (obviously we need to add more)
Definition: IpAlgTypes.hpp:22
Ipopt::NLPBoundsRemover::GetScalingParameters
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.
Ipopt::NLPBoundsRemover::GetSpaces
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.
Ipopt::NLPBoundsRemover::Eval_grad_f
virtual bool Eval_grad_f(const Vector &x, Vector &g_f)
Definition: IpNLPBoundsRemover.hpp:108
Ipopt::Matrix
Matrix Base Class.
Definition: IpMatrix.hpp:27
Ipopt::IpoptData
Class to organize all the data required by the algorithm.
Definition: IpIpoptData.hpp:83
Ipopt::NLPBoundsRemover::NLPBoundsRemover
NLPBoundsRemover()
Default Constructor.
x_L
Number * x_L
Lower bounds on variables.
Definition: IpStdCInterface.h:137
Ipopt::Index
int Index
Type of all indices of vectors, matrices etc.
Definition: IpTypes.hpp:19
Ipopt::NLPBoundsRemover::d_space_orig_
SmartPtr< const VectorSpace > d_space_orig_
Pointer to the original d space.
Definition: IpNLPBoundsRemover.hpp:251
Ipopt::NLPBoundsRemover::Eval_c
virtual bool Eval_c(const Vector &x, Vector &c)
Definition: IpNLPBoundsRemover.hpp:113
x_U
Number Number * x_U
Upper bounds on variables.
Definition: IpStdCInterface.h:137
x_scaling
Number Number * x_scaling
Definition: IpStdCInterface.h:210
Ipopt::NLPBoundsRemover::GetStartingPoint
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.
Ipopt::NLPBoundsRemover
This is an adaper for an NLP that converts variable bound constraints to inequality constraints...
Definition: IpNLPBoundsRemover.hpp:24
Ipopt::NLPBoundsRemover::GetBoundsInformation
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.
Ipopt::NLPBoundsRemover::GetWarmStartIterate
virtual bool GetWarmStartIterate(IteratesVector &warm_start_iterate)
Method for obtaining an entire iterate as a warmstart point.
Definition: IpNLPBoundsRemover.hpp:94
Ipopt::NLP
Brief Class Description.
Definition: IpNLP.hpp:31
Ipopt::NLPBoundsRemover::ProcessOptions
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...
Definition: IpNLPBoundsRemover.hpp:43
Ipopt::NLPBoundsRemover::Eval_d
virtual bool Eval_d(const Vector &x, Vector &d)
Ipopt::NLPBoundsRemover::operator=
void operator=(const NLPBoundsRemover &)
Overloaded Equals Operator.
Ipopt::NLPBoundsRemover::FinalizeSolution
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.
obj_scaling
Number obj_scaling
Definition: IpStdCInterface.h:210
Ipopt::NLPBoundsRemover::Px_l_orig_
SmartPtr< const Matrix > Px_l_orig_
Pointer to the expansion matrix for the lower x bounds.
Definition: IpNLPBoundsRemover.hpp:245
Ipopt::NLPBoundsRemover::nlp_
SmartPtr< NLP > nlp_
Pointer to the original NLP.
Definition: IpNLPBoundsRemover.hpp:242