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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 // $Id: IpIpoptCalculatedQuantities.hpp 2020 2011-06-16 20:46:16Z andreasw $
6 //
7 // Authors: Carl Laird, Andreas Waechter IBM 2004-08-13
8 
9 #ifndef __IPIPOPTCALCULATEDQUANTITIES_HPP__
10 #define __IPIPOPTCALCULATEDQUANTITIES_HPP__
11 
12 #include "IpSmartPtr.hpp"
13 #include "IpCachedResults.hpp"
14 
15 #include <string>
16 
17 namespace Ipopt
18 {
19  class IpoptNLP;
20  class IpoptData;
21  class Vector;
22  class Matrix;
23  class SymMatrix;
24  class Journalist;
25  class OptionsList;
26  class RegisteredOptions;
27 
29  enum ENormType {
30  NORM_1=0,
33  };
34 
41  {
42  public:
47  {}
48 
51  {}
53 
57  virtual bool Initialize(const Journalist& jnlst,
58  const OptionsList& options,
59  const std::string& prefix) = 0;
60 
61  private:
72 
74  void operator=(const IpoptAdditionalCq&);
76  };
77 
82  {
83  public:
84 
89  const SmartPtr<IpoptData>& ip_data);
93 
97  {
99  add_cq_ = add_cq;
100  }
101 
104  bool HaveAddCq()
105  {
106  return IsValid(add_cq_);
107  }
108 
112  bool Initialize(const Journalist& jnlst,
113  const OptionsList& options,
114  const std::string& prefix);
115 
139 
143  virtual Number curr_f();
145  virtual Number unscaled_curr_f();
147  virtual Number trial_f();
149  virtual Number unscaled_trial_f();
155 
161  virtual Number curr_barrier_obj();
165  virtual Number trial_barrier_obj();
166 
173 
181 
261 
267 
308 
310  virtual Number curr_primal_infeasibility(ENormType NormType);
312  virtual Number trial_primal_infeasibility(ENormType NormType);
313 
315  virtual Number curr_dual_infeasibility(ENormType NormType);
317  virtual Number trial_dual_infeasibility(ENormType NormType);
320 
323  virtual Number curr_complementarity(Number mu, ENormType NormType);
326  virtual Number trial_complementarity(Number mu, ENormType NormType);
330 
332  Number CalcCentralityMeasure(const Vector& compl_x_L,
333  const Vector& compl_x_U,
334  const Vector& compl_s_L,
335  const Vector& compl_s_U);
338 
343  virtual Number curr_nlp_error();
349 
352  virtual Number curr_barrier_error();
353 
369 
375  const Vector& delta_x,
376  const Vector& delta_s);
383  const Vector& delta_z_L,
384  const Vector& delta_z_U,
385  const Vector& delta_v_L,
386  const Vector& delta_v_U);
390  const Vector& delta_z_L,
391  const Vector& delta_z_U,
392  const Vector& delta_v_L,
393  const Vector& delta_v_U);
405  const Vector& delta_x_L,
406  const Vector& delta_x_U,
407  const Vector& delta_s_L,
408  const Vector& delta_s_U);
410 
416 
421 
425 
427  Number
428  CalcNormOfType(ENormType NormType,
429  std::vector<SmartPtr<const Vector> > vecs);
430 
432  Number
433  CalcNormOfType(ENormType NormType,
434  const Vector& vec1, const Vector& vec2);
435 
438  {
439  return constr_viol_normtype_;
440  }
441 
443  bool IsSquareProblem() const;
444 
448  {
449  return ip_nlp_;
450  }
451 
453  {
455  return *add_cq_;
456  }
457 
461  static void RegisterOptions(SmartPtr<RegisteredOptions> roptions);
463 
464  private:
475 
478 
482 
492 
513 
529 
537 
547 
572 
575 
610 
616 
622 
627 
630 
647 
660 
662  Vector& Tmp_x();
663  Vector& Tmp_s();
664  Vector& Tmp_c();
665  Vector& Tmp_d();
666  Vector& Tmp_x_L();
667  Vector& Tmp_x_U();
668  Vector& Tmp_s_L();
669  Vector& Tmp_s_U();
671 
675 
682  const Vector& x,
683  const Vector& x_bound);
688  const Vector& x,
689  const Vector& x_bound);
694  const Vector& slack_x_L,
695  const Vector& slack_x_U,
696  const Vector& slack_s_L,
697  const Vector& slack_s_U);
698 
701  const Vector& mult);
702 
704  Number CalcFracToBound(const Vector& slack_L,
705  Vector& tmp_L,
706  const Matrix& P_L,
707  const Vector& slack_U,
708  Vector& tmp_U,
709  const Matrix& P_U,
710  const Vector& delta,
711  Number tau);
712 
714  void ComputeOptimalityErrorScaling(const Vector& y_c, const Vector& y_d,
715  const Vector& z_L, const Vector& z_U,
716  const Vector& v_L, const Vector& v_U,
717  Number s_max,
718  Number& s_d, Number& s_c);
719 
724  const SmartPtr<const Vector>& bound,
725  const SmartPtr<const Vector>& curr_point,
726  const SmartPtr<const Vector>& multiplier);
727 
734  SmartPtr<const Vector>& dampind_x_U,
735  SmartPtr<const Vector>& dampind_s_L,
736  SmartPtr<const Vector>& dampind_s_U);
737 
744  bool in_restoration_phase();
745 
747  };
748 
749 } // namespace Ipopt
750 
751 #endif
SmartPtr< Vector > dampind_s_U_
Indicator vector for selecting the elements in s that have only upper bounds.
SmartPtr< Vector > dampind_s_L_
Indicator vector for selecting the elements in s that have only lower bounds.
virtual Number trial_primal_dual_system_error(Number mu)
Norm of the primal-dual system for a given mu (at trial iterate).
bool IsValid(const SmartPtr< U > &smart_ptr)
Definition: IpSmartPtr.hpp:579
CachedResults< Number > trial_avrg_compl_cache_
Cache for average of trial complementarity.
CachedResults< Number > curr_constraint_violation_cache_
Number * x
Input: Starting point Output: Optimal solution.
SmartPtr< const Vector > curr_slack_x_L()
Slacks for x_L (at current iterate)
SmartPtr< Vector > dampind_x_U_
Indicator vector for selecting the elements in x that have only upper bounds.
SmartPtr< const Vector > curr_jac_d_times_vec(const Vector &vec)
Product of Jacobian (evaluated at current point) of D with general vector.
CachedResults< SmartPtr< const Vector > > curr_relaxed_compl_x_L_cache_
SmartPtr< const Vector > curr_relaxed_compl_x_U()
Relaxed complementarity for x_U (for current iterate and current mu)
CachedResults< SmartPtr< const Vector > > curr_d_minus_s_cache_
SmartPtr< const Vector > curr_sigma_s()
Class for all IPOPT specific calculated quantities.
SmartPtr< const Vector > trial_jac_cT_times_vec(const Vector &vec)
Product of Jacobian (evaluated at trial point) of C transpose with general vector.
Number CalcNormOfType(ENormType NormType, std::vector< SmartPtr< const Vector > > vecs)
Compute the norm of a specific type of a set of vectors (uncached)
SmartPtr< const Vector > curr_compl_s_L()
Complementarity for s_L (for current iterate)
SmartPtr< const Vector > grad_kappa_times_damping_x()
Gradient of the damping term with respect to x (times kappa_d)
CachedResults< Number > trial_constraint_violation_cache_
virtual ~IpoptAdditionalCq()
Default destructor.
SmartPtr< const Vector > trial_grad_lag_s()
s-part of gradient of Lagrangian function (at trial point)
SmartPtr< const Vector > curr_relaxed_compl_s_U()
Relaxed complementarity for s_U (for current iterate and current mu)
CachedResults< Number > curr_centrality_measure_cache_
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_jac_cT_times_vec(const Vector &vec)
Product of Jacobian (evaluated at current point) of C transpose with general vector.
SmartPtr< const Vector > unscaled_curr_c()
unscaled c(x) (at current point)
virtual Number curr_centrality_measure()
Centrality measure at current point.
virtual Number curr_dual_infeasibility(ENormType NormType)
Dual infeasibility in a given norm (at current iterate)
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.
SmartPtr< const Vector > curr_d_minus_s()
d(x) - s (at current point)
SmartPtr< const Matrix > curr_jac_d()
Jacobian of d (at current point)
bool IsSquareProblem() const
Method returning true if this is a square problem.
Number curr_dual_frac_to_the_bound(Number tau)
Fraction to the boundary from (current) dual variables z and v for internal (current) step...
SmartPtr< const Vector > curr_compl_x_L()
Complementarity for x_L (for current iterate)
CachedResults< SmartPtr< Vector > > curr_slack_s_L_cache_
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)
virtual Number curr_f()
Value of objective function (at current point)
virtual Number trial_complementarity(Number mu, ENormType NormType)
Complementarity (for all complementarity conditions together) in a given norm (at trial iterate) ...
SmartPtr< const Vector > curr_jac_c_times_vec(const Vector &vec)
Product of Jacobian (evaluated at current point) of C with general vector.
SmartPtr< IpoptNLP > ip_nlp_
Ipopt NLP object.
SmartPtr< const Vector > curr_compl_x_U()
Complementarity for x_U (for current iterate)
SmartPtr< const Vector > CalcCompl(const Vector &slack, const Vector &mult)
Compute complementarity for slack / multiplier pair.
CachedResults< SmartPtr< Vector > > trial_slack_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 > > grad_kappa_times_damping_x_cache_
CachedResults< SmartPtr< const Matrix > > trial_jac_d_cache_
virtual Number trial_constraint_violation()
Constraint Violation (at trial point).
SmartPtr< const Vector > curr_relaxed_compl_x_L()
Relaxed complementarity for x_L (for current iterate and current mu)
CachedResults< Number > unscaled_curr_nlp_error_cache_
CachedResults< SmartPtr< const Vector > > curr_compl_x_L_cache_
double Number
Type of all numbers.
Definition: IpTypes.hpp:17
CachedResults< SmartPtr< const Vector > > trial_jac_dT_times_vec_cache_
SmartPtr< Vector > dampind_x_L_
Indicator vector for selecting the elements in x that have only lower bounds.
Vector Base Class.
Definition: IpVector.hpp:47
CachedResults< Number > trial_primal_infeasibility_cache_
CachedResults< SmartPtr< const Vector > > trial_c_cache_
SmartPtr< const Vector > curr_grad_lag_with_damping_s()
s-part of gradient of Lagrangian function (at current point) including linear damping term ...
SmartPtr< const Vector > trial_compl_s_L()
Complementarity for s_L (for trial iterate)
SmartPtr< const Vector > trial_compl_s_U()
Complementarity for s_U (for trial iterate)
virtual Number unscaled_curr_dual_infeasibility(ENormType NormType)
Unscaled dual infeasibility in a given norm (at current iterate)
virtual Number curr_primal_infeasibility(ENormType NormType)
Primal infeasibility in a given norm (at current iterate).
CachedResults< SmartPtr< const SymMatrix > > curr_exact_hessian_cache_
Cache for the exact Hessian.
CachedResults< SmartPtr< Vector > > trial_slack_s_U_cache_
CachedResults< SmartPtr< const Vector > > trial_d_cache_
Number s_max_
Parameter in formula for computing overall primal-dual optimality error.
CachedResults< Number > curr_primal_dual_system_error_cache_
CachedResults< SmartPtr< const Vector > > curr_grad_lag_with_damping_s_cache_
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.
CachedResults< SmartPtr< const Vector > > curr_sigma_x_cache_
CachedResults< SmartPtr< const Vector > > curr_relaxed_compl_s_U_cache_
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 > unscaled_trial_c()
unscaled c(x) (at trial point)
SmartPtr< const Vector > trial_compl_x_L()
Complementarity for x_L (for trial iterate)
CachedResults< SmartPtr< const Vector > > curr_relaxed_compl_x_U_cache_
Number mu_target_
Desired value of the barrier parameter.
virtual Number trial_barrier_obj()
Barrier Objective Function Value (at trial point with current mu)
CachedResults< Number > unscaled_trial_nlp_constraint_violation_cache_
CachedResults< SmartPtr< const Matrix > > trial_jac_c_cache_
CachedResults< SmartPtr< const Vector > > curr_jac_c_times_vec_cache_
CachedResults< SmartPtr< const Vector > > curr_compl_s_U_cache_
CachedResults< SmartPtr< const Vector > > curr_jac_dT_times_vec_cache_
CachedResults< SmartPtr< Vector > > curr_slack_x_U_cache_
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)
CachedResults< SmartPtr< const Vector > > curr_grad_barrier_obj_s_cache_
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 > curr_sigma_x()
bool in_restoration_phase()
Check if we are in the restoration phase.
CachedResults< SmartPtr< const Vector > > grad_kappa_times_damping_s_cache_
CachedResults< SmartPtr< const Vector > > trial_grad_f_cache_
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)
SmartPtr< const Vector > trial_d()
d(x) (at trial point)
virtual Number curr_barrier_error()
Total optimality error for the barrier problem at the current iterate, using scaling factors based on...
SmartPtr< const Vector > trial_slack_x_L()
Slacks for x_L (at trial point)
CachedResults< SmartPtr< Vector > > trial_slack_s_L_cache_
SmartPtr< const Vector > trial_slack_s_L()
Slacks for s_L (at trial point)
CachedResults< Number > curr_gradBarrTDelta_cache_
Cache for grad barrier obj.
SmartPtr< const Vector > trial_grad_lag_x()
x-part of gradient of Lagrangian function (at trial point)
Template class for Smart Pointers.
Definition: IpSmartPtr.hpp:172
CachedResults< SmartPtr< const Vector > > trial_d_minus_s_cache_
SmartPtr< const Matrix > trial_jac_c()
Jacobian of c (at trial point)
ReferencedObject class.
SmartPtr< const Vector > trial_c()
c(x) (at trial point)
This class stores a list of user set options.
void ResetAdjustedTrialSlacks()
Reset the flags for &quot;fudged&quot; slacks.
SmartPtr< IpoptAdditionalCq > add_cq_
Chen-Goldfarb specific calculated quantities.
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< Vector > > curr_slack_x_L_cache_
IpoptAdditionalCq()
Default Constructor.
CachedResults< SmartPtr< const Vector > > curr_grad_f_cache_
Number kappa_d_
Weighting factor for the linear damping term added to the barrier objective funciton.
virtual Number curr_complementarity(Number mu, ENormType NormType)
Complementarity (for all complementarity conditions together) in a given norm (at current iterate) ...
CachedResults< Number > primal_frac_to_the_bound_cache_
CachedResults< SmartPtr< const Vector > > trial_compl_x_U_cache_
CachedResults< SmartPtr< const Vector > > curr_d_cache_
SmartPtr< IpoptNLP > & GetIpoptNLP()
Method returning the IpoptNLP object.
Number slack_move_
fractional movement allowed in bounds
void operator=(const IpoptCalculatedQuantities &)
Overloaded Equals Operator.
CachedResults< Number > unscaled_curr_dual_infeasibility_cache_
CachedResults< SmartPtr< const Vector > > trial_compl_s_L_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. ...
Matrix Base Class.
Definition: IpMatrix.hpp:27
Cache Priority Enum.
SmartPtr< const Vector > grad_kappa_times_damping_s()
Gradient of the damping term with respect to s (times kappa_d)
SmartPtr< const Vector > curr_grad_lag_s()
s-part of gradient of Lagrangian function (at current point)
SmartPtr< const Vector > curr_slack_x_U()
Slacks for x_U (at current iterate)
virtual Number unscaled_curr_f()
Unscaled value of the objective function (at the current point)
CachedResults< SmartPtr< const Matrix > > curr_jac_d_cache_
SmartPtr< const Vector > curr_relaxed_compl_s_L()
Relaxed complementarity for s_L (for current iterate and current mu)
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...
virtual Number trial_f()
Value of objective function (at trial point)
SmartPtr< const Vector > curr_jac_dT_times_vec(const Vector &vec)
Product of Jacobian (evaluated at current point) of D transpose with general vector.
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< const Vector > curr_slack_s_U()
Slacks for s_U (at current iterate)
SmartPtr< const Vector > curr_c()
c(x) (at current point)
virtual Number unscaled_curr_nlp_constraint_violation(ENormType NormType)
Unscaled real constraint violation in a given norm (at current iterate).
CachedResults< Number > curr_dual_infeasibility_cache_
SmartPtr< const Matrix > curr_jac_c()
Jacobian of c (at current point)
virtual Number trial_primal_infeasibility(ENormType NormType)
Primal infeasibility in a given norm (at trial point)
CachedResults< SmartPtr< const Vector > > curr_compl_s_L_cache_
SmartPtr< const Vector > curr_grad_barrier_obj_x()
Gradient of barrier objective function with respect to x (at current point with current mu) ...
Number curr_gradBarrTDelta()
inner_product of current barrier obj.
SmartPtr< const Vector > trial_slack_x_U()
Slacks for x_U (at trial point)
CachedResults< SmartPtr< Vector > > curr_slack_s_U_cache_
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_...
CachedResults< Number > trial_primal_dual_system_error_cache_
int Index
Type of all indices of vectors, matrices etc.
Definition: IpTypes.hpp:19
SmartPtr< const Vector > trial_jac_dT_times_vec(const Vector &vec)
Product of Jacobian (evaluated at trial point) of D transpose with general vector.
SmartPtr< const Vector > trial_jac_cT_times_trial_y_c()
Product of Jacobian (evaluated at trial point) of C transpose with trial y_c.
SmartPtr< const Matrix > trial_jac_d()
Jacobian of d (at trial point)
#define DBG_ASSERT(test)
Definition: IpDebug.hpp:38
CachedResults< SmartPtr< const Vector > > curr_compl_x_U_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...
SmartPtr< const Vector > curr_compl_s_U()
Complementarity for s_U (for current iterate)
virtual bool Initialize(const Journalist &jnlst, const OptionsList &options, const std::string &prefix)=0
This method is called to initialize the global algorithmic parameters.
Number curr_avrg_compl()
average of current values of the complementarities
SmartPtr< const Vector > unscaled_curr_d()
unscaled d(x) (at current point)
Number trial_avrg_compl()
average of trial values of the complementarities
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)
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.
virtual Number trial_dual_infeasibility(ENormType NormType)
Dual infeasibility in a given norm (at trial iterate)
CachedResults< SmartPtr< const Vector > > curr_sigma_s_cache_
virtual Number unscaled_trial_f()
Unscaled value of the objective function (at the trial point)
CachedResults< SmartPtr< const Vector > > trial_grad_lag_x_cache_
CachedResults< SmartPtr< const Vector > > curr_jac_cT_times_vec_cache_
CachedResults< Number > curr_primal_infeasibility_cache_
void SetAddCq(SmartPtr< IpoptAdditionalCq > add_cq)
Method for setting pointer for additional calculated quantities.
SmartPtr< const Vector > curr_d()
d(x) (at current point)
CachedResults< SmartPtr< const Vector > > curr_c_cache_
CachedResults< SmartPtr< const Vector > > curr_relaxed_compl_s_L_cache_
bool initialize_called_
flag indicating if Initialize method has been called (for debugging)
CachedResults< SmartPtr< const Matrix > > curr_jac_c_cache_
CachedResults< SmartPtr< Vector > > trial_slack_x_U_cache_
virtual Number unscaled_trial_nlp_constraint_violation(ENormType NormType)
Unscaled real constraint violation in a given norm (at trial iterate).
CachedResults< Number > trial_dual_infeasibility_cache_
Class responsible for all message output.
CachedResults< Number > curr_avrg_compl_cache_
Cache for average of current complementarity.
CachedResults< SmartPtr< const Vector > > curr_grad_barrier_obj_x_cache_
virtual Number curr_barrier_obj()
Barrier Objective Function Value (at current iterate with current mu)
CachedResults< Number > curr_nlp_constraint_violation_cache_
bool warm_start_same_structure_
Flag indicating whether the TNLP with identical structure has already been solved before...
Index AdjustedTrialSlacks()
Indicating whether or not we &quot;fudged&quot; the slacks.
SmartPtr< const Vector > curr_jac_dT_times_curr_y_d()
Product of Jacobian (evaluated at current point) of D transpose with current y_d. ...
ENormType constr_viol_normtype() const
Norm type used for calculating constraint violation.
SmartPtr< const SymMatrix > curr_exact_hessian()
exact Hessian at current iterate (uncached)
SmartPtr< const Vector > curr_grad_f()
Gradient of objective function (at current point)
CachedResults< SmartPtr< const Vector > > curr_grad_lag_x_cache_
void operator=(const IpoptAdditionalCq &)
Overloaded Equals Operator.
SmartPtr< const Vector > curr_grad_lag_x()
x-part of gradient of Lagrangian function (at current point)
SmartPtr< IpoptData > ip_data_
Ipopt Data object.
bool Initialize(const Journalist &jnlst, const OptionsList &options, const std::string &prefix)
This method must be called to initialize the global algorithmic parameters.
virtual ~IpoptCalculatedQuantities()
Default destructor.
IpoptCalculatedQuantities()
Default Constructor.
virtual Number curr_constraint_violation()
Constraint Violation (at current iterate).
CachedResults< SmartPtr< const Vector > > trial_compl_x_L_cache_
SmartPtr< const Vector > curr_grad_lag_with_damping_x()
x-part of gradient of Lagrangian function (at current point) including linear damping term ...
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.
Base class for additional calculated quantities that is special to a particular type of algorithm...
CachedResults< SmartPtr< const Vector > > curr_jac_d_times_vec_cache_
SmartPtr< const Vector > trial_d_minus_s()
d(x) - s (at trial point)
SmartPtr< const Vector > trial_grad_f()
Gradient of objective function (at trial point)
SmartPtr< const Vector > trial_slack_s_U()
Slacks for s_U (at trial point)
virtual Number curr_primal_dual_system_error(Number mu)
Norm of the primal-dual system for a given mu (at current iterate).
CachedResults< SmartPtr< const Vector > > curr_grad_lag_s_cache_
ENormType constr_viol_normtype_
Norm type to be used when calculating the constraint violation.
CachedResults< SmartPtr< const Vector > > curr_grad_lag_with_damping_x_cache_
CachedResults< SmartPtr< const Vector > > trial_jac_cT_times_vec_cache_
SmartPtr< const Vector > curr_grad_barrier_obj_s()
Gradient of barrier objective function with respect to s (at current point with current mu) ...
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< Number > unscaled_curr_nlp_constraint_violation_cache_
CachedResults< SmartPtr< const Vector > > trial_grad_lag_s_cache_
bool HaveAddCq()
Method detecting if additional object for calculated quantities has already been set.
virtual Number curr_nlp_constraint_violation(ENormType NormType)
Real constraint violation in a given norm (at current iterate).
Vector & Tmp_x()
Accessor methods for the temporary vectors.
static void RegisterOptions(SmartPtr< RegisteredOptions > roptions)
Methods for IpoptType.