Ipopt 3.11.9
IpNLP.hpp
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1// Copyright (C) 2004, 2006 International Business Machines and others.
2// All Rights Reserved.
3// This code is published under the Eclipse Public License.
4//
5// $Id: IpNLP.hpp 1861 2010-12-21 21:34:47Z andreasw $
6//
7// Authors: Carl Laird, Andreas Waechter IBM 2004-08-13
8
9#ifndef __IPNLP_HPP__
10#define __IPNLP_HPP__
11
12#include "IpUtils.hpp"
13#include "IpVector.hpp"
14#include "IpSmartPtr.hpp"
15#include "IpMatrix.hpp"
16#include "IpSymMatrix.hpp"
17#include "IpOptionsList.hpp"
18#include "IpAlgTypes.hpp"
19#include "IpReturnCodes.hpp"
20
21namespace Ipopt
22{
23 // forward declarations
24 class IpoptData;
25 class IpoptCalculatedQuantities;
26 class IteratesVector;
27
31 class NLP : public ReferencedObject
32 {
33 public:
38 {}
39
41 virtual ~NLP()
42 {}
44
47 DECLARE_STD_EXCEPTION(USER_SCALING_NOT_IMPLEMENTED);
50
56 virtual bool ProcessOptions(const OptionsList& options,
57 const std::string& prefix)
58 {
59 return true;
60 }
61
76 SmartPtr<const MatrixSpace>& Jac_c_space,
77 SmartPtr<const MatrixSpace>& Jac_d_space,
78 SmartPtr<const SymMatrixSpace>& Hess_lagrangian_space)=0;
79
81 virtual bool GetBoundsInformation(const Matrix& Px_L,
82 Vector& x_L,
83 const Matrix& Px_U,
84 Vector& x_U,
85 const Matrix& Pd_L,
86 Vector& d_L,
87 const Matrix& Pd_U,
88 Vector& d_U)=0;
89
93 virtual bool GetStartingPoint(
95 bool need_x,
97 bool need_y_c,
99 bool need_y_d,
101 bool need_z_L,
103 bool need_z_U
104 )=0;
105
109 virtual bool GetWarmStartIterate(IteratesVector& warm_start_iterate)
110 {
111 return false;
112 }
114
118 virtual bool Eval_f(const Vector& x, Number& f) = 0;
119
120 virtual bool Eval_grad_f(const Vector& x, Vector& g_f) = 0;
121
122 virtual bool Eval_c(const Vector& x, Vector& c) = 0;
123
124 virtual bool Eval_jac_c(const Vector& x, Matrix& jac_c) = 0;
125
126 virtual bool Eval_d(const Vector& x, Vector& d) = 0;
127
128 virtual bool Eval_jac_d(const Vector& x, Matrix& jac_d) = 0;
129
130 virtual bool Eval_h(const Vector& x,
131 Number obj_factor,
132 const Vector& yc,
133 const Vector& yd,
134 SymMatrix& h) = 0;
136
145 virtual void FinalizeSolution(SolverReturn status,
146 const Vector& x, const Vector& z_L,
147 const Vector& z_U,
148 const Vector& c, const Vector& d,
149 const Vector& y_c, const Vector& y_d,
150 Number obj_value,
151 const IpoptData* ip_data,
153 {}
154
171 Index iter, Number obj_value,
172 Number inf_pr, Number inf_du,
173 Number mu, Number d_norm,
174 Number regularization_size,
175 Number alpha_du, Number alpha_pr,
176 Index ls_trials,
177 const IpoptData* ip_data,
179 {
180 return true;
181 }
183
189 const SmartPtr<const VectorSpace> x_space,
190 const SmartPtr<const VectorSpace> c_space,
191 const SmartPtr<const VectorSpace> d_space,
194 SmartPtr<Vector>& c_scaling,
195 SmartPtr<Vector>& d_scaling) const
196 {
197 THROW_EXCEPTION(USER_SCALING_NOT_IMPLEMENTED,
198 "You have set options for user provided scaling, but have"
199 " not implemented GetScalingParameters in the NLP interface");
200 }
202
216 virtual void
218 SmartPtr<Matrix>& P_approx)
219 {
220 approx_space = NULL;
221 P_approx = NULL;
222 }
223
224 private:
234 NLP(const NLP&);
235
237 void operator=(const NLP&);
239 };
240
241} // namespace Ipopt
242
243#endif
#define THROW_EXCEPTION(__except_type, __msg)
AlgorithmMode
enum to indicate the mode in which the algorithm is
Number * x
Input: Starting point Output: Optimal solution.
Number Number * x_scaling
Number obj_scaling
Number * x_L
Lower bounds on variables.
Number Number * x_U
Upper bounds on variables.
Class for all IPOPT specific calculated quantities.
Class to organize all the data required by the algorithm.
Definition: IpIpoptData.hpp:84
Specialized CompoundVector class specifically for the algorithm iterates.
Matrix Base Class.
Definition: IpMatrix.hpp:28
Brief Class Description.
Definition: IpNLP.hpp:32
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.
Definition: IpNLP.hpp:145
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)=0
Method for obtaining the bounds information.
virtual bool Eval_h(const Vector &x, Number obj_factor, const Vector &yc, const Vector &yd, SymMatrix &h)=0
DECLARE_STD_EXCEPTION(USER_SCALING_NOT_IMPLEMENTED)
Exceptions.
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: IpNLP.hpp:56
virtual bool Eval_grad_f(const Vector &x, Vector &g_f)=0
DECLARE_STD_EXCEPTION(INVALID_NLP)
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)=0
Method for obtaining the starting point for all the iterates.
NLP()
Default constructor.
Definition: IpNLP.hpp:37
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)=0
Method for creating the derived vector / matrix types.
virtual bool Eval_d(const Vector &x, Vector &d)=0
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.
Definition: IpNLP.hpp:188
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: IpNLP.hpp:170
NLP(const NLP &)
Copy Constructor.
virtual bool Eval_c(const Vector &x, Vector &c)=0
void operator=(const NLP &)
Overloaded Equals Operator.
virtual bool GetWarmStartIterate(IteratesVector &warm_start_iterate)
Method for obtaining an entire iterate as a warmstart point.
Definition: IpNLP.hpp:109
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: IpNLP.hpp:217
virtual ~NLP()
Default destructor.
Definition: IpNLP.hpp:41
virtual bool Eval_jac_d(const Vector &x, Matrix &jac_d)=0
virtual bool Eval_f(const Vector &x, Number &f)=0
virtual bool Eval_jac_c(const Vector &x, Matrix &jac_c)=0
This class stores a list of user set options.
ReferencedObject class.
Template class for Smart Pointers.
Definition: IpSmartPtr.hpp:183
This is the base class for all derived symmetric matrix types.
Definition: IpSymMatrix.hpp:24
Vector Base Class.
Definition: IpVector.hpp:48
SolverReturn
enum for the return from the optimize algorithm (obviously we need to add more)
Definition: IpAlgTypes.hpp:22
int Index
Type of all indices of vectors, matrices etc.
Definition: IpTypes.hpp:19
double Number
Type of all numbers.
Definition: IpTypes.hpp:17