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Diffstat (limited to 'newstructure/thirdparty/linux/include/coin/IpOrigIpoptNLP.hpp')
| -rw-r--r-- | newstructure/thirdparty/linux/include/coin/IpOrigIpoptNLP.hpp | 488 |
1 files changed, 0 insertions, 488 deletions
diff --git a/newstructure/thirdparty/linux/include/coin/IpOrigIpoptNLP.hpp b/newstructure/thirdparty/linux/include/coin/IpOrigIpoptNLP.hpp deleted file mode 100644 index 41b10fa..0000000 --- a/newstructure/thirdparty/linux/include/coin/IpOrigIpoptNLP.hpp +++ /dev/null @@ -1,488 +0,0 @@ -// Copyright (C) 2004, 2010 International Business Machines and others. -// All Rights Reserved. -// This code is published under the Eclipse Public License. -// -// $Id: IpOrigIpoptNLP.hpp 2594 2015-08-09 14:31:05Z stefan $ -// -// Authors: Carl Laird, Andreas Waechter IBM 2004-08-13 - -#ifndef __IPORIGIPOPTNLP_HPP__ -#define __IPORIGIPOPTNLP_HPP__ - -#include "IpIpoptNLP.hpp" -#include "IpException.hpp" -#include "IpTimingStatistics.hpp" - -namespace Ipopt -{ - - /** enumeration for the Hessian information type. */ - enum HessianApproximationType { - EXACT=0, - LIMITED_MEMORY - }; - - /** enumeration for the Hessian approximation space. */ - enum HessianApproximationSpace { - NONLINEAR_VARS=0, - ALL_VARS - }; - - /** This class maps the traditional NLP into - * something that is more useful by Ipopt. - * This class takes care of storing the - * calculated model results, handles caching, - * and (some day) takes care of addition of slacks. - */ - class OrigIpoptNLP : public IpoptNLP - { - public: - /**@name Constructors/Destructors */ - //@{ - OrigIpoptNLP(const SmartPtr<const Journalist>& jnlst, - const SmartPtr<NLP>& nlp, - const SmartPtr<NLPScalingObject>& nlp_scaling); - - /** Default destructor */ - virtual ~OrigIpoptNLP(); - //@} - - /** Initialize - overloaded from IpoptNLP */ - virtual bool Initialize(const Journalist& jnlst, - const OptionsList& options, - const std::string& prefix); - - /** Initialize (create) structures for - * the iteration data */ - virtual bool InitializeStructures(SmartPtr<Vector>& x, - bool init_x, - SmartPtr<Vector>& y_c, - bool init_y_c, - SmartPtr<Vector>& y_d, - bool init_y_d, - SmartPtr<Vector>& z_L, - bool init_z_L, - SmartPtr<Vector>& z_U, - bool init_z_U, - SmartPtr<Vector>& v_L, - SmartPtr<Vector>& v_U - ); - - /** Method accessing the GetWarmStartIterate of the NLP */ - virtual bool GetWarmStartIterate(IteratesVector& warm_start_iterate) - { - return nlp_->GetWarmStartIterate(warm_start_iterate); - } - /** Accessor methods for model data */ - //@{ - /** Objective value */ - virtual Number f(const Vector& x); - - /** Objective value (depending in mu) - incorrect version for - * OrigIpoptNLP */ - virtual Number f(const Vector& x, Number mu); - - /** Gradient of the objective */ - virtual SmartPtr<const Vector> grad_f(const Vector& x); - - /** Gradient of the objective (depending in mu) - incorrect - * version for OrigIpoptNLP */ - virtual SmartPtr<const Vector> grad_f(const Vector& x, Number mu); - - /** Equality constraint residual */ - virtual SmartPtr<const Vector> c(const Vector& x); - - /** Jacobian Matrix for equality constraints */ - virtual SmartPtr<const Matrix> jac_c(const Vector& x); - - /** Inequality constraint residual (reformulated - * as equalities with slacks */ - virtual SmartPtr<const Vector> d(const Vector& x); - - /** Jacobian Matrix for inequality constraints*/ - virtual SmartPtr<const Matrix> jac_d(const Vector& x); - - /** Hessian of the Lagrangian */ - virtual SmartPtr<const SymMatrix> h(const Vector& x, - Number obj_factor, - const Vector& yc, - const Vector& yd - ); - - /** Hessian of the Lagrangian (depending in mu) - incorrect - * version for OrigIpoptNLP */ - virtual SmartPtr<const SymMatrix> h(const Vector& x, - Number obj_factor, - const Vector& yc, - const Vector& yd, - Number mu); - - /** Provides a Hessian matrix from the correct matrix space with - * uninitialized values. This can be used in LeastSquareMults to - * obtain a "zero Hessian". */ - virtual SmartPtr<const SymMatrix> uninitialized_h(); - - /** Lower bounds on x */ - virtual SmartPtr<const Vector> x_L() const - { - return x_L_; - } - - /** Permutation matrix (x_L_ -> x) */ - virtual SmartPtr<const Matrix> Px_L() const - { - return Px_L_; - } - - /** Upper bounds on x */ - virtual SmartPtr<const Vector> x_U() const - { - return x_U_; - } - - /** Permutation matrix (x_U_ -> x */ - virtual SmartPtr<const Matrix> Px_U() const - { - return Px_U_; - } - - /** Lower bounds on d */ - virtual SmartPtr<const Vector> d_L() const - { - return d_L_; - } - - /** Permutation matrix (d_L_ -> d) */ - virtual SmartPtr<const Matrix> Pd_L() const - { - return Pd_L_; - } - - /** Upper bounds on d */ - virtual SmartPtr<const Vector> d_U() const - { - return d_U_; - } - - /** Permutation matrix (d_U_ -> d */ - virtual SmartPtr<const Matrix> Pd_U() const - { - return Pd_U_; - } - - virtual SmartPtr<const SymMatrixSpace> HessianMatrixSpace() const - { - return h_space_; - } - - virtual SmartPtr<const VectorSpace> x_space() const - { - return x_space_; - } - //@} - - /** Accessor method for vector/matrix spaces pointers */ - virtual void 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 adapting the variable bounds. This is called if - * slacks are becoming too small */ - virtual void AdjustVariableBounds(const Vector& new_x_L, - const Vector& new_x_U, - const Vector& new_d_L, - const Vector& new_d_U); - - /** @name Counters for the number of function evaluations. */ - //@{ - virtual Index f_evals() const - { - return f_evals_; - } - virtual Index grad_f_evals() const - { - return grad_f_evals_; - } - virtual Index c_evals() const - { - return c_evals_; - } - virtual Index jac_c_evals() const - { - return jac_c_evals_; - } - virtual Index d_evals() const - { - return d_evals_; - } - virtual Index jac_d_evals() const - { - return jac_d_evals_; - } - virtual Index h_evals() const - { - return h_evals_; - } - //@} - - /** Solution Routines - overloaded from IpoptNLP*/ - //@{ - 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); - 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, - SmartPtr<const IpoptData> ip_data, - SmartPtr<IpoptCalculatedQuantities> ip_cq); - //@} - - /** @name Methods for IpoptType */ - //@{ - /** Called by IpoptType to register the options */ - static void RegisterOptions(SmartPtr<RegisteredOptions> roptions); - //@} - - /** Accessor method to the underlying NLP */ - SmartPtr<NLP> nlp() - { - return nlp_; - } - - /**@name Methods related to function evaluation timing. */ - //@{ - - /** Reset the timing statistics */ - void ResetTimes(); - - void PrintTimingStatistics(Journalist& jnlst, - EJournalLevel level, - EJournalCategory category) const; - - const TimedTask& f_eval_time() const - { - return f_eval_time_; - } - const TimedTask& grad_f_eval_time() const - { - return grad_f_eval_time_; - } - const TimedTask& c_eval_time() const - { - return c_eval_time_; - } - const TimedTask& jac_c_eval_time() const - { - return jac_c_eval_time_; - } - const TimedTask& d_eval_time() const - { - return d_eval_time_; - } - const TimedTask& jac_d_eval_time() const - { - return jac_d_eval_time_; - } - const TimedTask& h_eval_time() const - { - return h_eval_time_; - } - - Number TotalFunctionEvaluationCpuTime() const; - Number TotalFunctionEvaluationSysTime() const; - Number TotalFunctionEvaluationWallclockTime() const; - //@} - - private: - /** journalist */ - SmartPtr<const Journalist> jnlst_; - - /** Pointer to the NLP */ - SmartPtr<NLP> nlp_; - - /** Necessary Vector/Matrix spaces */ - //@{ - 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> h_space_; - - SmartPtr<const MatrixSpace> scaled_jac_c_space_; - SmartPtr<const MatrixSpace> scaled_jac_d_space_; - SmartPtr<const SymMatrixSpace> scaled_h_space_; - //@} - /**@name Storage for Model Quantities */ - //@{ - /** Objective function */ - CachedResults<Number> f_cache_; - - /** Gradient of the objective function */ - CachedResults<SmartPtr<const Vector> > grad_f_cache_; - - /** Equality constraint residuals */ - CachedResults<SmartPtr<const Vector> > c_cache_; - - /** Jacobian Matrix for equality constraints - * (current iteration) */ - CachedResults<SmartPtr<const Matrix> > jac_c_cache_; - - /** Inequality constraint residual (reformulated - * as equalities with slacks */ - CachedResults<SmartPtr<const Vector> > d_cache_; - - /** Jacobian Matrix for inequality constraints - * (current iteration) */ - CachedResults<SmartPtr<const Matrix> > jac_d_cache_; - - /** Hessian of the lagrangian - * (current iteration) */ - CachedResults<SmartPtr<const SymMatrix> > h_cache_; - - /** Unscaled version of x vector */ - CachedResults<SmartPtr<const Vector> > unscaled_x_cache_; - - /** Lower bounds on x */ - SmartPtr<const Vector> x_L_; - - /** Permutation matrix (x_L_ -> x) */ - SmartPtr<const Matrix> Px_L_; - - /** Upper bounds on x */ - SmartPtr<const Vector> x_U_; - - /** Permutation matrix (x_U_ -> x */ - SmartPtr<const Matrix> Px_U_; - - /** Lower bounds on d */ - SmartPtr<const Vector> d_L_; - - /** Permutation matrix (d_L_ -> d) */ - SmartPtr<const Matrix> Pd_L_; - - /** Upper bounds on d */ - SmartPtr<const Vector> d_U_; - - /** Permutation matrix (d_U_ -> d */ - SmartPtr<const Matrix> Pd_U_; - - /** Original unmodified lower bounds on x */ - SmartPtr<const Vector> orig_x_L_; - - /** Original unmodified upper bounds on x */ - SmartPtr<const Vector> orig_x_U_; - //@} - - /**@name Default Compiler Generated Methods - * (Hidden to avoid implicit creation/calling). - * These methods are not implemented and - * we do not want the compiler to implement - * them for us, so we declare them private - * and do not define them. This ensures that - * they will not be implicitly created/called. */ - //@{ - /** Default Constructor */ - OrigIpoptNLP(); - - /** Copy Constructor */ - OrigIpoptNLP(const OrigIpoptNLP&); - - /** Overloaded Equals Operator */ - void operator=(const OrigIpoptNLP&); - //@} - - /** @name auxilliary functions */ - //@{ - /** relax the bounds by a relative move of relax_bound_factor. - * Here, relax_bound_factor should be negative (or zero) for - * lower bounds, and positive (or zero) for upper bounds. - */ - void relax_bounds(Number bound_relax_factor, Vector& bounds); - /** Method for getting the unscaled version of the x vector */ - SmartPtr<const Vector> get_unscaled_x(const Vector& x); - //@} - - /** @name Algorithmic parameters */ - //@{ - /** relaxation factor for the bounds */ - Number bound_relax_factor_; - /** Flag indicating whether the primal variables should be - * projected back into original bounds are optimization. */ - bool honor_original_bounds_; - /** Flag indicating whether the TNLP with identical structure has - * already been solved before. */ - bool warm_start_same_structure_; - /** Flag indicating what Hessian information is to be used. */ - HessianApproximationType hessian_approximation_; - /** Flag indicating in which space Hessian is to be approximated. */ - HessianApproximationSpace hessian_approximation_space_; - /** Flag indicating whether it is desired to check if there are - * Nan or Inf entries in first and second derivative matrices. */ - bool check_derivatives_for_naninf_; - /** Flag indicating if we need to ask for equality constraint - * Jacobians only once */ - bool jac_c_constant_; - /** Flag indicating if we need to ask for inequality constraint - * Jacobians only once */ - bool jac_d_constant_; - /** Flag indicating if we need to ask for Hessian only once */ - bool hessian_constant_; - //@} - - /** @name Counters for the function evaluations */ - //@{ - Index f_evals_; - Index grad_f_evals_; - Index c_evals_; - Index jac_c_evals_; - Index d_evals_; - Index jac_d_evals_; - Index h_evals_; - //@} - - /** Flag indicating if initialization method has been called */ - bool initialized_; - - /**@name Timing statistics for the function evaluations. */ - //@{ - TimedTask f_eval_time_; - TimedTask grad_f_eval_time_; - TimedTask c_eval_time_; - TimedTask jac_c_eval_time_; - TimedTask d_eval_time_; - TimedTask jac_d_eval_time_; - TimedTask h_eval_time_; - //@} - }; - -} // namespace Ipopt - -#endif |