Ipopt Documentation  
IpIpoptCalculatedQuantities.hpp
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1 // Copyright (C) 2004, 2011 International Business Machines and others.
2 // All Rights Reserved.
3 // This code is published under the Eclipse Public License.
4 //
5 // Authors: Carl Laird, Andreas Waechter IBM 2004-08-13
6 
7 #ifndef __IPIPOPTCALCULATEDQUANTITIES_HPP__
8 #define __IPIPOPTCALCULATEDQUANTITIES_HPP__
9 
10 #include "IpSmartPtr.hpp"
11 #include "IpCachedResults.hpp"
12 
13 #include <string>
14 
15 namespace Ipopt
16 {
17 class IpoptNLP;
18 class IpoptData;
19 class Vector;
20 class Matrix;
21 class SymMatrix;
22 class Journalist;
23 class OptionsList;
24 class RegisteredOptions;
25 
28 {
29  NORM_1 = 0,
31  NORM_MAX
32 };
33 
42 {
43 public:
46 
48  { }
49 
52  { }
54 
60  virtual bool Initialize(
61  const Journalist& jnlst,
62  const OptionsList& options,
63  const std::string& prefix
64  ) = 0;
65 
66 private:
77 
79  const IpoptAdditionalCq&);
80 
82  void operator=(
83  const IpoptAdditionalCq&);
85 };
86 
89 {
90 public:
91 
94 
96  const SmartPtr<IpoptNLP>& ip_nlp,
97  const SmartPtr<IpoptData>& ip_data
98  );
102 
108  void SetAddCq(
110  )
111  {
112  DBG_ASSERT(!HaveAddCq());
113  add_cq_ = add_cq;
114  }
115 
119  bool HaveAddCq()
120  {
121  return IsValid(add_cq_);
122  }
123 
130  const Journalist& jnlst,
131  const OptionsList& options,
132  const std::string& prefix
133  );
134 
137 
158 
161 
162  virtual Number curr_f();
166  virtual Number trial_f();
174 
177 
185 
194 
200 
203 
233  const Vector& vec
234  );
239  const Vector& vec
240  );
245  const Vector& vec
246  );
251  const Vector& vec
252  );
273  const Vector& vec
274  );
279  const Vector& vec
280  );
300  ENormType NormType
301  );
307  ENormType NormType
308  );
314  ENormType NormType
315  );
317 
320 
323 
326 
366 
369  ENormType NormType
370  );
373  ENormType NormType
374  );
375 
378  ENormType NormType
379  );
382  ENormType NormType
383  );
386  ENormType NormType
387  );
388 
393  Number mu,
394  ENormType NormType
395  );
400  Number mu,
401  ENormType NormType
402  );
407  Number mu,
408  ENormType NormType
409  );
410 
413  const Vector& compl_x_L,
414  const Vector& compl_x_U,
415  const Vector& compl_s_L,
416  const Vector& compl_s_U
417  );
420 
436 
441 
450  Number mu
451  );
460  Number mu
461  );
463 
466 
470  Number tau,
471  const Vector& delta_x,
472  const Vector& delta_s
473  );
478  Number tau
479  );
484  Number tau,
485  const Vector& delta_z_L,
486  const Vector& delta_z_U,
487  const Vector& delta_v_L,
488  const Vector& delta_v_U
489  );
494  Number tau,
495  const Vector& delta_z_L,
496  const Vector& delta_z_U,
497  const Vector& delta_v_L,
498  const Vector& delta_v_U
499  );
504  Number tau
505  );
517  Number tau,
518  const Vector& delta_x_L,
519  const Vector& delta_x_U,
520  const Vector& delta_s_L,
521  const Vector& delta_s_U
522  );
524 
530 
535 
540 
542  Number
544  ENormType NormType,
545  std::vector<SmartPtr<const Vector> > vecs
546  );
547 
549  Number
551  ENormType NormType,
552  const Vector& vec1,
553  const Vector& vec2
554  );
555 
558  {
559  return constr_viol_normtype_;
560  }
561 
563  bool IsSquareProblem() const;
564 
570  {
571  return ip_nlp_;
572  }
573 
575  {
576  DBG_ASSERT(IsValid(add_cq_));
577  return *add_cq_;
578  }
579 
581  static void RegisterOptions(
583  );
584 
585 private:
596 
598 
602  );
603 
605  void operator=(
607  );
609 
612 
619 
626 
645 
661 
669 
679 
704 
707 
742 
748 
754 
759 
762 
766 
783 
798 
809 
814 
817 
821  const Matrix& P,
822  const Vector& x,
823  const Vector& x_bound
824  );
829  const Matrix& P,
830  const Vector& x,
831  const Vector& x_bound
832  );
837  Number mu,
838  const Vector& slack_x_L,
839  const Vector& slack_x_U,
840  const Vector& slack_s_L,
841  const Vector& slack_s_U
842  );
843 
846  const Vector& slack,
847  const Vector& mult
848  );
849 
852  const Vector& slack_L,
853  Vector& tmp_L,
854  const Matrix& P_L,
855  const Vector& slack_U,
856  Vector& tmp_U,
857  const Matrix& P_U,
858  const Vector& delta,
859  Number tau
860  );
861 
864  const Vector& y_c,
865  const Vector& y_d,
866  const Vector& z_L,
867  const Vector& z_U,
868  const Vector& v_L,
869  const Vector& v_U,
870  Number s_max,
871  Number& s_d,
872  Number& s_c
873  );
874 
882  SmartPtr<Vector>& slack,
883  const SmartPtr<const Vector>& bound,
884  const SmartPtr<const Vector>& curr_point,
885  const SmartPtr<const Vector>& multiplier
886  );
887 
896  SmartPtr<const Vector>& dampind_x_L,
897  SmartPtr<const Vector>& dampind_x_U,
898  SmartPtr<const Vector>& dampind_s_L,
899  SmartPtr<const Vector>& dampind_s_U
900  );
901 
913 
915 };
916 
917 } // namespace Ipopt
918 
919 #endif
#define DBG_ASSERT(test)
Definition: IpDebug.hpp:27
Templated class for Cached Results.
Base class for additional calculated quantities that is special to a particular type of algorithm,...
void operator=(const IpoptAdditionalCq &)
Default Assignment Operator.
virtual bool Initialize(const Journalist &jnlst, const OptionsList &options, const std::string &prefix)=0
This method is called to initialize the global algorithmic parameters.
IpoptAdditionalCq(const IpoptAdditionalCq &)
Copy Constructor.
Class for all IPOPT specific calculated quantities.
CachedResults< SmartPtr< const Matrix > > trial_jac_d_cache_
CachedResults< Number > curr_constraint_violation_cache_
SmartPtr< const Vector > curr_jac_cT_times_vec(const Vector &vec)
Product of Jacobian (evaluated at current point) of C transpose with general vector.
SmartPtr< const Vector > unscaled_trial_c()
unscaled c(x) (at trial point)
SmartPtr< IpoptData > ip_data_
Ipopt Data object.
CachedResults< SmartPtr< const Vector > > curr_relaxed_compl_s_U_cache_
SmartPtr< const Vector > CalcCompl(const Vector &slack, const Vector &mult)
Compute complementarity for slack / multiplier pair.
CachedResults< SmartPtr< const Vector > > curr_jac_dT_times_vec_cache_
Number curr_primal_frac_to_the_bound(Number tau)
Fraction to the boundary from (current) primal variables x and s for internal (current) step.
CachedResults< SmartPtr< const Vector > > trial_c_cache_
virtual Number curr_nlp_constraint_violation(ENormType NormType)
Real constraint violation in a given norm (at current iterate).
virtual Number unscaled_curr_nlp_constraint_violation(ENormType NormType)
Unscaled real constraint violation in a given norm (at current iterate).
SmartPtr< const Vector > trial_compl_s_U()
Complementarity for s_U (for trial iterate)
SmartPtr< const Vector > curr_grad_f()
Gradient of objective function (at current point)
IpoptCalculatedQuantities()
Default Constructor.
ENormType constr_viol_normtype_
Norm type to be used when calculating the constraint violation.
SmartPtr< const Vector > trial_d_minus_s()
d(x) - s (at trial point)
CachedResults< SmartPtr< Vector > > curr_slack_s_L_cache_
SmartPtr< const Vector > curr_compl_x_L()
Complementarity for x_L (for current iterate)
CachedResults< SmartPtr< const Vector > > curr_sigma_x_cache_
virtual Number curr_centrality_measure()
Centrality measure at current point.
CachedResults< SmartPtr< const Vector > > curr_compl_s_U_cache_
bool Initialize(const Journalist &jnlst, const OptionsList &options, const std::string &prefix)
This method must be called to initialize the global algorithmic parameters.
CachedResults< SmartPtr< const Vector > > trial_grad_lag_s_cache_
virtual Number unscaled_curr_dual_infeasibility(ENormType NormType)
Unscaled dual infeasibility in a given norm (at current iterate)
CachedResults< SmartPtr< const Vector > > trial_compl_x_L_cache_
bool IsSquareProblem() const
Method returning true if this is a square problem.
CachedResults< Number > unscaled_trial_nlp_constraint_violation_cache_
SmartPtr< const Vector > curr_compl_s_L()
Complementarity for s_L (for current iterate)
CachedResults< SmartPtr< const Vector > > curr_grad_lag_with_damping_x_cache_
SmartPtr< const Vector > curr_relaxed_compl_s_U()
Relaxed complementarity for s_U (for current iterate and current mu)
SmartPtr< const Vector > curr_relaxed_compl_x_U()
Relaxed complementarity for x_U (for current iterate and current mu)
Number curr_dual_frac_to_the_bound(Number tau)
Fraction to the boundary from (current) dual variables z and v for internal (current) step.
Number dual_frac_to_the_bound(Number tau, const Vector &delta_z_L, const Vector &delta_z_U, const Vector &delta_v_L, const Vector &delta_v_U)
Fraction to the boundary from (current) dual variables z and v for a given step.
CachedResults< SmartPtr< const Vector > > curr_d_minus_s_cache_
SmartPtr< const Vector > trial_slack_s_L()
Slacks for s_L (at trial point)
Number CalcNormOfType(ENormType NormType, const Vector &vec1, const Vector &vec2)
Compute the norm of a specific type of two vectors (uncached)
virtual Number trial_constraint_violation()
Constraint Violation (at trial point).
CachedResults< SmartPtr< const SymMatrix > > curr_exact_hessian_cache_
Cache for the exact Hessian.
SmartPtr< const Vector > curr_sigma_s()
bool warm_start_same_structure_
Flag indicating whether the TNLP with identical structure has already been solved before.
SmartPtr< const Vector > curr_slack_x_U()
Slacks for x_U (at current iterate)
SmartPtr< const Vector > trial_slack_x_U()
Slacks for x_U (at trial point)
CachedResults< SmartPtr< const Vector > > trial_compl_x_U_cache_
CachedResults< SmartPtr< const Vector > > curr_grad_barrier_obj_x_cache_
CachedResults< Number > curr_primal_dual_system_error_cache_
CachedResults< SmartPtr< Vector > > trial_slack_s_U_cache_
bool initialize_called_
flag indicating if Initialize method has been called (for debugging)
CachedResults< Number > curr_centrality_measure_cache_
CachedResults< Number > curr_gradBarrTDelta_cache_
Cache for grad barrier obj.
SmartPtr< const Matrix > trial_jac_c()
Jacobian of c (at trial point)
IpoptCalculatedQuantities(const IpoptCalculatedQuantities &)
Copy Constructor.
CachedResults< Number > curr_dual_infeasibility_cache_
CachedResults< Number > unscaled_curr_nlp_error_cache_
virtual Number curr_primal_infeasibility(ENormType NormType)
Primal infeasibility in a given norm (at current iterate).
SmartPtr< Vector > dampind_s_L_
Indicator vector for selecting the elements in s that have only lower bounds.
CachedResults< SmartPtr< const Vector > > trial_jac_dT_times_vec_cache_
Number uncached_dual_frac_to_the_bound(Number tau, const Vector &delta_z_L, const Vector &delta_z_U, const Vector &delta_v_L, const Vector &delta_v_U)
Fraction to the boundary from (current) dual variables z and v for a given step, without caching.
SmartPtr< const Vector > trial_jac_dT_times_trial_y_d()
Product of Jacobian (evaluated at trial point) of D transpose with trial y_d.
SmartPtr< const Vector > curr_slack_s_L()
Slacks for s_L (at current iterate)
CachedResults< SmartPtr< const Vector > > trial_jac_cT_times_vec_cache_
virtual Number curr_constraint_violation()
Constraint Violation (at current iterate).
virtual Number trial_complementarity(Number mu, ENormType NormType)
Complementarity (for all complementarity conditions together) in a given norm (at trial iterate)
SmartPtr< const Vector > trial_jac_dT_times_vec(const Vector &vec)
Product of Jacobian (evaluated at trial point) of D transpose with general vector.
virtual Number trial_f()
Value of objective function (at trial point)
CachedResults< Number > primal_frac_to_the_bound_cache_
SmartPtr< const Vector > curr_grad_lag_x()
x-part of gradient of Lagrangian function (at current point)
virtual Number unscaled_trial_f()
Unscaled value of the objective function (at the trial point)
SmartPtr< Vector > dampind_x_U_
Indicator vector for selecting the elements in x that have only upper bounds.
SmartPtr< const Vector > curr_grad_lag_s()
s-part of gradient of Lagrangian function (at current point)
void ComputeDampingIndicators(SmartPtr< const Vector > &dampind_x_L, SmartPtr< const Vector > &dampind_x_U, SmartPtr< const Vector > &dampind_s_L, SmartPtr< const Vector > &dampind_s_U)
Computes the indicator vectors that can be used to filter out those entries in the slack_....
SmartPtr< Vector > dampind_s_U_
Indicator vector for selecting the elements in s that have only upper bounds.
CachedResults< SmartPtr< const Vector > > curr_grad_f_cache_
CachedResults< SmartPtr< const Vector > > curr_relaxed_compl_x_U_cache_
CachedResults< Number > curr_avrg_compl_cache_
Cache for average of current complementarity.
CachedResults< SmartPtr< Vector > > trial_slack_x_L_cache_
virtual Number curr_barrier_error()
Total optimality error for the barrier problem at the current iterate, using scaling factors based on...
SmartPtr< const Vector > curr_d()
d(x) (at current point)
SmartPtr< const Vector > trial_jac_cT_times_trial_y_c()
Product of Jacobian (evaluated at trial point) of C transpose with trial y_c.
virtual Number unscaled_curr_nlp_error()
Total optimality error for the original NLP at the current iterate, but using no scaling based on mul...
SmartPtr< const Vector > curr_sigma_x()
SmartPtr< const Vector > curr_compl_x_U()
Complementarity for x_U (for current iterate)
Number kappa_d_
Weighting factor for the linear damping term added to the barrier objective function.
virtual Number trial_primal_infeasibility(ENormType NormType)
Primal infeasibility in a given norm (at trial point)
CachedResults< SmartPtr< const Vector > > trial_d_minus_s_cache_
Index CalculateSafeSlack(SmartPtr< Vector > &slack, const SmartPtr< const Vector > &bound, const SmartPtr< const Vector > &curr_point, const SmartPtr< const Vector > &multiplier)
Check if slacks are becoming too small.
CachedResults< SmartPtr< const Matrix > > curr_jac_d_cache_
CachedResults< Number > trial_primal_dual_system_error_cache_
CachedResults< SmartPtr< const Vector > > curr_sigma_s_cache_
CachedResults< Number > unscaled_curr_dual_infeasibility_cache_
void SetAddCq(SmartPtr< IpoptAdditionalCq > add_cq)
Method for setting pointer for additional calculated quantities.
CachedResults< Number > trial_avrg_compl_cache_
Cache for average of trial complementarity.
Number s_max_
Parameter in formula for computing overall primal-dual optimality error.
void operator=(const IpoptCalculatedQuantities &)
Default Assignment Operator.
SmartPtr< const Vector > curr_grad_lag_with_damping_s()
s-part of gradient of Lagrangian function (at current point) including linear damping term
Number curr_gradBarrTDelta()
inner_product of current barrier obj.
Number trial_avrg_compl()
average of trial values of the complementarities
SmartPtr< const Vector > grad_kappa_times_damping_x()
Gradient of the damping term with respect to x (times kappa_d)
SmartPtr< const Vector > trial_grad_lag_x()
x-part of gradient of Lagrangian function (at trial point)
virtual Number curr_f()
Value of objective function (at current point)
virtual Number trial_primal_dual_system_error(Number mu)
Norm of the primal-dual system for a given mu (at trial iterate).
CachedResults< Number > trial_primal_infeasibility_cache_
virtual Number trial_barrier_obj()
Barrier Objective Function Value (at trial point with current mu)
CachedResults< SmartPtr< Vector > > curr_slack_x_U_cache_
SmartPtr< const Vector > curr_relaxed_compl_x_L()
Relaxed complementarity for x_L (for current iterate and current mu)
SmartPtr< Vector > CalcSlack_U(const Matrix &P, const Vector &x, const Vector &x_bound)
Compute new vector containing the slack to a upper bound (uncached)
CachedResults< Number > trial_dual_infeasibility_cache_
bool in_restoration_phase()
Check if we are in the restoration phase.
CachedResults< SmartPtr< const Vector > > trial_grad_f_cache_
SmartPtr< const Vector > curr_compl_s_U()
Complementarity for s_U (for current iterate)
SmartPtr< const Vector > unscaled_curr_d()
unscaled d(x) (at current point)
Number CalcFracToBound(const Vector &slack_L, Vector &tmp_L, const Matrix &P_L, const Vector &slack_U, Vector &tmp_U, const Matrix &P_U, const Vector &delta, Number tau)
Compute fraction to the boundary parameter for lower and upper bounds.
Number CalcNormOfType(ENormType NormType, std::vector< SmartPtr< const Vector > > vecs)
Compute the norm of a specific type of a set of vectors (uncached)
CachedResults< Number > curr_nlp_constraint_violation_cache_
CachedResults< SmartPtr< Vector > > trial_slack_s_L_cache_
virtual Number curr_barrier_obj()
Barrier Objective Function Value (at current iterate with current mu)
SmartPtr< const Vector > curr_grad_barrier_obj_s()
Gradient of barrier objective function with respect to s (at current point with current mu)
SmartPtr< const Vector > trial_slack_x_L()
Slacks for x_L (at trial point)
SmartPtr< const Matrix > curr_jac_d()
Jacobian of d (at current point)
SmartPtr< Vector > dampind_x_L_
Indicator vector for selecting the elements in x that have only lower bounds.
SmartPtr< const Vector > curr_jac_dT_times_vec(const Vector &vec)
Product of Jacobian (evaluated at current point) of D transpose with general vector.
SmartPtr< const SymMatrix > curr_exact_hessian()
exact Hessian at current iterate (uncached)
SmartPtr< const Vector > curr_grad_lag_with_damping_x()
x-part of gradient of Lagrangian function (at current point) including linear damping term
Number CalcBarrierTerm(Number mu, const Vector &slack_x_L, const Vector &slack_x_U, const Vector &slack_s_L, const Vector &slack_s_U)
Compute barrier term at given point (uncached)
SmartPtr< const Vector > curr_c()
c(x) (at current point)
CachedResults< SmartPtr< const Vector > > curr_jac_d_times_vec_cache_
CachedResults< SmartPtr< const Vector > > curr_compl_s_L_cache_
Number slack_move_
fractional movement allowed in bounds
SmartPtr< const Vector > trial_jac_cT_times_vec(const Vector &vec)
Product of Jacobian (evaluated at trial point) of C transpose with general vector.
virtual Number curr_primal_dual_system_error(Number mu)
Norm of the primal-dual system for a given mu (at current iterate).
IpoptCalculatedQuantities(const SmartPtr< IpoptNLP > &ip_nlp, const SmartPtr< IpoptData > &ip_data)
Constructor.
SmartPtr< const Vector > unscaled_curr_c()
unscaled c(x) (at current point)
CachedResults< Number > curr_primal_infeasibility_cache_
Number primal_frac_to_the_bound(Number tau, const Vector &delta_x, const Vector &delta_s)
Fraction to the boundary from (current) primal variables x and s for a given step.
Number mu_target_
Desired value of the barrier parameter.
CachedResults< SmartPtr< const Vector > > curr_grad_lag_s_cache_
CachedResults< SmartPtr< const Vector > > trial_compl_s_L_cache_
SmartPtr< const Matrix > trial_jac_d()
Jacobian of d (at trial point)
SmartPtr< Vector > CalcSlack_L(const Matrix &P, const Vector &x, const Vector &x_bound)
Compute new vector containing the slack to a lower bound (uncached)
CachedResults< SmartPtr< const Matrix > > curr_jac_c_cache_
SmartPtr< const Vector > curr_d_minus_s()
d(x) - s (at current point)
virtual Number curr_nlp_error()
Total optimality error for the original NLP at the current iterate, using scaling factors based on mu...
SmartPtr< const Vector > curr_jac_c_times_vec(const Vector &vec)
Product of Jacobian (evaluated at current point) of C with general vector.
Index AdjustedTrialSlacks()
Indicating whether or not we "fudged" the slacks.
CachedResults< SmartPtr< const Vector > > trial_d_cache_
CachedResults< SmartPtr< Vector > > trial_slack_x_U_cache_
CachedResults< SmartPtr< const Vector > > curr_d_cache_
SmartPtr< const Vector > trial_d()
d(x) (at trial point)
ENormType constr_viol_normtype() const
Norm type used for calculating constraint violation.
SmartPtr< const Vector > curr_grad_barrier_obj_x()
Gradient of barrier objective function with respect to x (at current point with current mu)
CachedResults< SmartPtr< const Vector > > curr_c_cache_
bool HaveAddCq()
Method detecting if additional object for calculated quantities has already been set.
virtual Number unscaled_curr_complementarity(Number mu, ENormType NormType)
Complementarity (for all complementarity conditions together) in a given norm (at current iterate) wi...
SmartPtr< const Vector > trial_compl_x_L()
Complementarity for x_L (for trial iterate)
virtual Number unscaled_trial_nlp_constraint_violation(ENormType NormType)
Unscaled real constraint violation in a given norm (at trial iterate).
CachedResults< SmartPtr< const Vector > > trial_grad_lag_x_cache_
SmartPtr< IpoptAdditionalCq > add_cq_
Chen-Goldfarb specific calculated quantities.
SmartPtr< const Vector > trial_compl_s_L()
Complementarity for s_L (for trial iterate)
SmartPtr< const Vector > curr_jac_d_times_vec(const Vector &vec)
Product of Jacobian (evaluated at current point) of D with general vector.
CachedResults< Number > trial_constraint_violation_cache_
SmartPtr< IpoptNLP > ip_nlp_
Ipopt NLP object.
SmartPtr< const Vector > trial_compl_x_U()
Complementarity for x_U (for trial iterate)
CachedResults< SmartPtr< const Vector > > trial_compl_s_U_cache_
CachedResults< SmartPtr< const Vector > > curr_relaxed_compl_x_L_cache_
CachedResults< SmartPtr< const Vector > > grad_kappa_times_damping_x_cache_
void ComputeOptimalityErrorScaling(const Vector &y_c, const Vector &y_d, const Vector &z_L, const Vector &z_U, const Vector &v_L, const Vector &v_U, Number s_max, Number &s_d, Number &s_c)
Compute the scaling factors for the optimality error.
SmartPtr< const Vector > curr_relaxed_compl_s_L()
Relaxed complementarity for s_L (for current iterate and current mu)
virtual ~IpoptCalculatedQuantities()
Destructor.
Number uncached_slack_frac_to_the_bound(Number tau, const Vector &delta_x_L, const Vector &delta_x_U, const Vector &delta_s_L, const Vector &delta_s_U)
Fraction to the boundary from (current) slacks for a given step in the slacks.
SmartPtr< IpoptNLP > & GetIpoptNLP()
Method returning the IpoptNLP object.
CachedResults< SmartPtr< const Vector > > curr_jac_cT_times_vec_cache_
SmartPtr< const Vector > trial_grad_f()
Gradient of objective function (at trial point)
CachedResults< SmartPtr< const Vector > > curr_compl_x_L_cache_
Number CalcCentralityMeasure(const Vector &compl_x_L, const Vector &compl_x_U, const Vector &compl_s_L, const Vector &compl_s_U)
Centrality measure (in spirit of the -infinity-neighborhood.
CachedResults< SmartPtr< const Vector > > curr_grad_lag_x_cache_
virtual Number unscaled_curr_f()
Unscaled value of the objective function (at the current point)
Vector & Tmp_x()
Accessor methods for the temporary vectors.
virtual Number curr_dual_infeasibility(ENormType NormType)
Dual infeasibility in a given norm (at current iterate)
CachedResults< SmartPtr< const Vector > > grad_kappa_times_damping_s_cache_
SmartPtr< const Vector > trial_grad_lag_s()
s-part of gradient of Lagrangian function (at trial point)
virtual Number trial_dual_infeasibility(ENormType NormType)
Dual infeasibility in a given norm (at trial iterate)
CachedResults< SmartPtr< Vector > > curr_slack_x_L_cache_
SmartPtr< const Vector > grad_kappa_times_damping_s()
Gradient of the damping term with respect to s (times kappa_d)
SmartPtr< const Vector > trial_c()
c(x) (at trial point)
Number curr_avrg_compl()
average of current values of the complementarities
CachedResults< Number > unscaled_curr_nlp_constraint_violation_cache_
CachedResults< SmartPtr< const Vector > > curr_grad_barrier_obj_s_cache_
virtual Number curr_complementarity(Number mu, ENormType NormType)
Complementarity (for all complementarity conditions together) in a given norm (at current iterate)
SmartPtr< const Vector > curr_slack_x_L()
Slacks for x_L (at current iterate)
SmartPtr< const Vector > curr_slack_s_U()
Slacks for s_U (at current iterate)
CachedResults< SmartPtr< const Vector > > curr_compl_x_U_cache_
CachedResults< SmartPtr< const Vector > > curr_relaxed_compl_s_L_cache_
CachedResults< SmartPtr< Vector > > curr_slack_s_U_cache_
SmartPtr< const Vector > curr_jac_cT_times_curr_y_c()
Product of Jacobian (evaluated at current point) of C transpose with current y_c.
CachedResults< SmartPtr< const Vector > > curr_grad_lag_with_damping_s_cache_
CachedResults< SmartPtr< const Matrix > > trial_jac_c_cache_
SmartPtr< const Vector > curr_jac_dT_times_curr_y_d()
Product of Jacobian (evaluated at current point) of D transpose with current y_d.
CachedResults< SmartPtr< const Vector > > curr_jac_c_times_vec_cache_
SmartPtr< const Vector > trial_slack_s_U()
Slacks for s_U (at trial point)
SmartPtr< const Matrix > curr_jac_c()
Jacobian of c (at current point)
static void RegisterOptions(SmartPtr< RegisteredOptions > roptions)
Called by IpoptType to register the options.
void ResetAdjustedTrialSlacks()
Reset the flags for "fudged" slacks.
Class responsible for all message output.
Matrix Base Class.
Definition: IpMatrix.hpp:28
This class stores a list of user set options.
Storing the reference count of all the smart pointers that currently reference it.
Template class for Smart Pointers.
Definition: IpSmartPtr.hpp:172
Vector Base Class.
Definition: IpVector.hpp:48
#define IPOPTLIB_EXPORT
This file contains a base class for all exceptions and a set of macros to help with exceptions.
bool IsValid(const SmartPtr< U > &smart_ptr)
Definition: IpSmartPtr.hpp:674
int Index
Type of all indices of vectors, matrices etc.
Definition: IpTypes.hpp:17
double Number
Type of all numbers.
Definition: IpTypes.hpp:15