Ipopt  3.11.9
IpTNLPAdapter.hpp
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1 // Copyright (C) 2004, 2008 International Business Machines and others.
2 // All Rights Reserved.
3 // This code is published under the Eclipse Public License.
4 //
5 // $Id: IpTNLPAdapter.hpp 1861 2010-12-21 21:34:47Z andreasw $
6 //
7 // Authors: Carl Laird, Andreas Waechter IBM 2004-08-13
8 
9 #ifndef __IPTNLPADAPTER_HPP__
10 #define __IPTNLPADAPTER_HPP__
11 
12 #include "IpNLP.hpp"
13 #include "IpTNLP.hpp"
14 #include "IpOrigIpoptNLP.hpp"
15 #include <list>
16 
17 namespace Ipopt
18 {
19 
20  // forward declarations
21  class ExpansionMatrix;
22  class ExpansionMatrixSpace;
23  class IteratesVector;
24  class TDependencyDetector;
25 
30  class TNLPAdapter : public NLP
31  {
32  public:
37  const SmartPtr<const Journalist> jnlst = NULL);
38 
40  virtual ~TNLPAdapter();
42 
45  DECLARE_STD_EXCEPTION(INVALID_TNLP);
46  DECLARE_STD_EXCEPTION(ERROR_IN_TNLP_DERIVATIVE_TEST);
48 
51  virtual bool ProcessOptions(const OptionsList& options,
52  const std::string& prefix);
53 
56  virtual bool GetSpaces(SmartPtr<const VectorSpace>& x_space,
59  SmartPtr<const VectorSpace>& x_l_space,
60  SmartPtr<const MatrixSpace>& px_l_space,
61  SmartPtr<const VectorSpace>& x_u_space,
62  SmartPtr<const MatrixSpace>& px_u_space,
63  SmartPtr<const VectorSpace>& d_l_space,
64  SmartPtr<const MatrixSpace>& pd_l_space,
65  SmartPtr<const VectorSpace>& d_u_space,
66  SmartPtr<const MatrixSpace>& pd_u_space,
67  SmartPtr<const MatrixSpace>& Jac_c_space,
68  SmartPtr<const MatrixSpace>& Jac_d_space,
69  SmartPtr<const SymMatrixSpace>& Hess_lagrangian_space);
70 
72  virtual bool GetBoundsInformation(const Matrix& Px_L,
73  Vector& x_L,
74  const Matrix& Px_U,
75  Vector& x_U,
76  const Matrix& Pd_L,
77  Vector& d_L,
78  const Matrix& Pd_U,
79  Vector& d_U);
80 
83  virtual bool GetStartingPoint(
85  bool need_x,
86  SmartPtr<Vector> y_c,
87  bool need_y_c,
88  SmartPtr<Vector> y_d,
89  bool need_y_d,
90  SmartPtr<Vector> z_L,
91  bool need_z_L,
92  SmartPtr<Vector> z_U,
93  bool need_z_U
94  );
95 
98  virtual bool GetWarmStartIterate(IteratesVector& warm_start_iterate);
100 
103  virtual bool Eval_f(const Vector& x, Number& f);
104 
105  virtual bool Eval_grad_f(const Vector& x, Vector& g_f);
106 
107  virtual bool Eval_c(const Vector& x, Vector& c);
108 
109  virtual bool Eval_jac_c(const Vector& x, Matrix& jac_c);
110 
111  virtual bool Eval_d(const Vector& x, Vector& d);
112 
113  virtual bool Eval_jac_d(const Vector& x, Matrix& jac_d);
114 
115  virtual bool Eval_h(const Vector& x,
116  Number obj_factor,
117  const Vector& yc,
118  const Vector& yd,
119  SymMatrix& h);
120 
121  virtual void GetScalingParameters(
122  const SmartPtr<const VectorSpace> x_space,
123  const SmartPtr<const VectorSpace> c_space,
124  const SmartPtr<const VectorSpace> d_space,
127  SmartPtr<Vector>& c_scaling,
128  SmartPtr<Vector>& d_scaling) const;
130 
133  virtual void FinalizeSolution(SolverReturn status,
134  const Vector& x,
135  const Vector& z_L, const Vector& z_U,
136  const Vector& c, const Vector& d,
137  const Vector& y_c, const Vector& y_d,
138  Number obj_value,
139  const IpoptData* ip_data,
141 
143  Index iter, Number obj_value,
144  Number inf_pr, Number inf_du,
145  Number mu, Number d_norm,
146  Number regularization_size,
147  Number alpha_du, Number alpha_pr,
148  Index ls_trials,
149  const IpoptData* ip_data,
152 
154  virtual void
156  SmartPtr<Matrix>& P_approx);
157 
160  {
164  };
165 
168  {
173  };
174 
177  {
180  };
181 
184  Index deriv_test_start_index);
185 
190 
193  {
194  return tnlp_;
195  }
196 
203  void ResortX(const Vector& x, Number* x_orig);
204  void ResortG(const Vector& c, const Vector& d, Number *g_orig);
205  void ResortBnds(const Vector& x_L, Number* x_L_orig,
206  const Vector& x_U, Number* x_U_orig);
208 
209  private:
220 
222  void operator=(const TNLPAdapter&);
224 
228  const Index* x_not_fixed_map,
229  const Number* x_l, const Number* x_u,
230  const Number* g_l, const Number* g_u,
231  Index n_c, const Index* c_map,
232  std::list<Index>& c_deps);
233 
237 
240 
244 
253  /* Determines relaxation of fixing bound for RELAX_BOUNDS. */
255  /* Maximal slack for one-sidedly bounded variables. If a
256  * variable has only one bound, say a lower bound xL, then an
257  * upper bound xL + max_onesided_bound_slack_. If this value is
258  * zero, no upper bound is added. */
259  /* Took this out: Number max_onesided_bound_slack_; */
289 
293 
316 
319 
337 
346 
355 
358  bool update_local_x(const Vector& x);
359  bool update_local_lambda(const Vector& y_c, const Vector& y_d);
361 
365  bool internal_eval_g(bool new_x);
366  bool internal_eval_jac_g(bool new_x);
368 
373  void initialize_findiff_jac(const Index* iRow, const Index* jCol);
375 
382 
386 
390 
394 
398 
401 
405 
423  };
424 
425 } // namespace Ipopt
426 
427 #endif
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
This class stores a list of user set options.
Template class for Smart Pointers.
Definition: IpSmartPtr.hpp:183
This is the base class for all derived symmetric matrix types.
Definition: IpSymMatrix.hpp:24
This class Adapts the TNLP interface so it looks like an NLP interface.
Number point_perturbation_radius_
Maximal perturbation of the initial point.
bool dependency_detection_with_rhs_
Flag indicating if rhs should be considered during dependency detection.
DECLARE_STD_EXCEPTION(ERROR_IN_TNLP_DERIVATIVE_TEST)
SmartPtr< const MatrixSpace > Jac_c_space_
Index nz_jac_c_
non-zeros of the jacobian of c
SmartPtr< const Journalist > jnlst_
Journalist.
Number findiff_perturbation_
Size of the perturbation for the derivative approximation.
bool derivative_test_print_all_
Flag indicating if all test values should be printed, or only those violating the threshold.
Index * x_fixed_map_
Position of fixed variables.
SmartPtr< const MatrixSpace > pd_u_space_
Index nz_jac_d_
non-zeros of the jacobian of d
TNLPAdapter(const SmartPtr< TNLP > tnlp, const SmartPtr< const Journalist > jnlst=NULL)
Default constructor.
DerivativeTestEnum derivative_test_
Enum indicating whether and which derivative test should be performed at starting point.
Index nz_jac_c_no_extra_
non-zeros of the jacobian of c without added constraints for fixed variables.
Number * full_g_
copy of lambda (yc & yd)
Index * findiff_jac_ja_
Ordered by columns, for each column the row indices in Jacobian.
SmartPtr< const VectorSpace > d_space_
bool update_local_x(const Vector &x)
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.
SmartPtr< const VectorSpace > x_l_space_
SmartPtr< const VectorSpace > x_u_space_
Index n_x_fixed_
Number of fixed variables.
FixedVariableTreatmentEnum fixed_variable_treatment_
Flag indicating how fixed variables should be handled.
SmartPtr< ExpansionMatrixSpace > P_x_full_x_space_
void ResortG(const Vector &c, const Vector &d, Number *g_orig)
bool warm_start_same_structure_
Flag indicating whether the TNLP with identical structure has already been solved before.
virtual bool Eval_grad_f(const Vector &x, Vector &g_f)
TaggedObject::Tag y_d_tag_for_iterates_
virtual bool Eval_jac_d(const Vector &x, Matrix &jac_d)
Number derivative_test_tol_
Relative threshold for marking deviation from finite difference test.
SmartPtr< ExpansionMatrix > P_x_x_L_
Expansion from fixed x_L (ipopt) to full x.
static void RegisterOptions(SmartPtr< RegisteredOptions > roptions)
void operator=(const TNLPAdapter &)
Overloaded Equals Operator.
Index n_full_x_
full dimension of x (fixed + non-fixed)
Index * findiff_jac_postriplet_
Position of entry in original triplet matrix.
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 MatrixSpace > pd_l_space_
JacobianApproxEnum
Enum for specifying technique for computing Jacobian.
Index nz_full_h_
number of non-zeros in full-size Hessian
SmartPtr< const VectorSpace > c_space_
TNLP::IndexStyleEnum index_style_
Numbering style of variables and constraints.
Number nlp_lower_bound_inf_
Value for a lower bound that denotes -infinity.
bool internal_eval_g(bool new_x)
SmartPtr< const MatrixSpace > px_u_space_
Index n_full_g_
full dimension of g (c + d)
TaggedObject::Tag x_tag_for_g_
SmartPtr< ExpansionMatrixSpace > P_x_x_L_space_
virtual void GetQuasiNewtonApproximationSpaces(SmartPtr< VectorSpace > &approx_space, SmartPtr< Matrix > &P_approx)
Method returning information on quasi-Newton approximation.
SmartPtr< TNLP > tnlp_
Pointer to the TNLP class (class specific to Number* vectors and harwell triplet matrices)
void initialize_findiff_jac(const Index *iRow, const Index *jCol)
Initialize sparsity structure for finite difference Jacobian.
SmartPtr< const VectorSpace > d_u_space_
Number derivative_test_perturbation_
Size of the perturbation for the derivative test.
Index findiff_jac_nnz_
Number of unique nonzeros in constraint Jacobian.
Number * full_lambda_
copy of the full x vector (fixed & non-fixed)
TaggedObject::Tag x_tag_for_jac_g_
Number nlp_upper_bound_inf_
Value for a upper bound that denotes infinity.
Number * jac_g_
copy of g (c & d)
bool CheckDerivatives(DerivativeTestEnum deriv_test, Index deriv_test_start_index)
Method for performing the derivative test.
Number * c_rhs_
the values for the full jacobian of g
virtual bool Eval_d(const Vector &x, Vector &d)
SmartPtr< const VectorSpace > d_l_space_
Number * findiff_x_u_
Copy of the upper bounds.
Index nz_full_jac_g_
number of non-zeros in full-size Jacobian of g
virtual ~TNLPAdapter()
Default destructor.
Index derivative_test_first_index_
Index of first quantity to be checked.
SmartPtr< ExpansionMatrix > P_x_full_x_
Expansion from fixed x (ipopt) to full x.
FixedVariableTreatmentEnum
Enum for treatment of fixed variables option.
SmartPtr< ExpansionMatrix > P_c_g_
SmartPtr< ExpansionMatrix > P_d_g_
SmartPtr< ExpansionMatrixSpace > P_x_x_U_space_
void ResortX(const Vector &x, Number *x_orig)
Sort the primal variables, and add the fixed values in x.
TNLPAdapter(const TNLPAdapter &)
Copy Constructor.
bool DetermineDependentConstraints(Index n_x_var, const Index *x_not_fixed_map, const Number *x_l, const Number *x_u, const Number *g_l, const Number *g_u, Index n_c, const Index *c_map, std::list< Index > &c_deps)
bool internal_eval_jac_g(bool new_x)
virtual bool GetWarmStartIterate(IteratesVector &warm_start_iterate)
Method for obtaining an entire iterate as a warmstart point.
virtual bool Eval_jac_c(const Vector &x, Matrix &jac_c)
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.
TaggedObject::Tag x_tag_for_iterates_
void ResortBnds(const Vector &x_L, Number *x_L_orig, const Vector &x_U, Number *x_U_orig)
SmartPtr< ExpansionMatrix > P_x_x_U_
Expansion from fixed x_U (ipopt) to full x.
SmartPtr< const SymMatrixSpace > Hess_lagrangian_space_
SmartPtr< TDependencyDetector > dependency_detector_
Object that can be used to detect linearly dependent rows in the equality constraint Jacobian.
virtual bool Eval_h(const Vector &x, Number obj_factor, const Vector &yc, const Vector &yd, SymMatrix &h)
Number * findiff_x_l_
Copy of the lower bounds.
SmartPtr< ExpansionMatrixSpace > P_c_g_space_
Expansion from c only (ipopt) to full ampl c.
SmartPtr< const VectorSpace > x_space_
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.
JacobianApproxEnum jacobian_approximation_
Flag indicating how Jacobian is computed.
Index * findiff_jac_ia_
Start position for nonzero indices in ja for each column of Jacobian.
virtual bool Eval_f(const Vector &x, Number &f)
SmartPtr< ExpansionMatrixSpace > P_d_g_space_
Expansion from d only (ipopt) to full ampl d.
HessianApproximationType hessian_approximation_
Flag indicating what Hessian information is to be used.
TaggedObject::Tag y_c_tag_for_iterates_
Number tol_
Overall convergence tolerance.
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.
SmartPtr< TNLP > tnlp() const
Accessor method for the underlying TNLP.
bool update_local_lambda(const Vector &y_c, const Vector &y_d)
SmartPtr< const MatrixSpace > Jac_d_space_
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 (Do not delete these, the ).
Index num_linear_variables_
Number of linear variables.
Index nz_h_
number of non-zeros in the non-fixed-size Hessian
virtual bool Eval_c(const Vector &x, Vector &c)
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 MatrixSpace > px_l_space_
DECLARE_STD_EXCEPTION(INVALID_TNLP)
DerivativeTestEnum
Enum for specifying which derivative test is to be performed.
IndexStyleEnum
overload this method to return the number of variables and constraints, and the number of non-zeros i...
Definition: IpTNLP.hpp:80
unsigned int Tag
Type for the Tag values.
Vector Base Class.
Definition: IpVector.hpp:48
HessianApproximationType
enumeration for the Hessian information type.
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