9 #ifndef __IPIPOPTNLP_HPP__
10 #define __IPIPOPTNLP_HPP__
47 const std::string& prefix)
224 Number regularization_size,
bool IsValid(const SmartPtr< U > &smart_ptr)
Number * x
Input: Starting point Output: Optimal solution.
void operator=(const IpoptNLP &)
Overloaded Equals Operator.
Specialized CompoundVector class specifically for the algorithm iterates.
Class for all IPOPT specific calculated quantities.
IpoptNLP(const SmartPtr< NLPScalingObject > nlp_scaling)
virtual SmartPtr< const Matrix > Pd_U() const =0
Permutation matrix (d_U_ -> d.
virtual Index h_evals() const =0
virtual Index c_evals() const =0
virtual SmartPtr< const SymMatrixSpace > HessianMatrixSpace() const =0
Accessor method to obtain the MatrixSpace for the Hessian matrix (or it's approximation) ...
virtual bool GetWarmStartIterate(IteratesVector &warm_start_iterate)=0
Method accessing the GetWarmStartIterate of the NLP.
AlgorithmMode
enum to indicate the mode in which the algorithm is
virtual SmartPtr< const SymMatrix > uninitialized_h()=0
Provides a Hessian matrix from the correct matrix space with uninitialized values.
double Number
Type of all numbers.
SmartPtr< NLPScalingObject > NLP_scaling() const
Returns the scaling strategy object.
virtual Index grad_f_evals() const =0
virtual Index f_evals() const =0
virtual ~IpoptNLP()
Default destructor.
virtual SmartPtr< const SymMatrix > h(const Vector &x, Number obj_factor, const Vector &yc, const Vector &yd)=0
Hessian of the Lagrangian.
virtual SmartPtr< const Vector > d_L() const =0
Lower bounds on d.
SmartPtr< NLPScalingObject > nlp_scaling_
Template class for Smart Pointers.
This class stores a list of user set options.
virtual SmartPtr< const Matrix > jac_d(const Vector &x)=0
Jacobian Matrix for inequality constraints.
virtual bool Initialize(const Journalist &jnlst, const OptionsList &options, const std::string &prefix)
Initialization method.
SolverReturn
enum for the return from the optimize algorithm (obviously we need to add more)
virtual void AdjustVariableBounds(const Vector &new_x_L, const Vector &new_x_U, const Vector &new_d_L, const Vector &new_d_U)=0
Method for adapting the variable bounds.
virtual Index jac_c_evals() const =0
Class to organize all the data required by the algorithm.
DECLARE_STD_EXCEPTION(Eval_Error)
thrown if there is any error evaluating values from the nlp
int Index
Type of all indices of vectors, matrices etc.
virtual SmartPtr< const Vector > d_U() const =0
Upper bounds on d.
virtual bool objective_depends_on_mu() const
Method for telling the IpoptCalculatedQuantities class whether the objective function depends on the ...
virtual SmartPtr< const Vector > x_U() const =0
Upper bounds on x.
virtual Number f(const Vector &x)=0
Accessor methods for model data.
virtual SmartPtr< const Matrix > jac_c(const Vector &x)=0
Jacobian Matrix for equality constraints.
virtual SmartPtr< const Matrix > Px_U() const =0
Permutation matrix (x_U_ -> x.
virtual SmartPtr< const VectorSpace > x_space() const =0
x_space
virtual SmartPtr< const Matrix > Pd_L() const =0
Permutation matrix (d_L_ -> d)
Class responsible for all message output.
virtual SmartPtr< const Matrix > Px_L() const =0
Permutation matrix (x_L_ -> x)
virtual SmartPtr< const Vector > grad_f(const Vector &x)=0
Gradient of the objective.
virtual SmartPtr< const Vector > d(const Vector &x)=0
Inequality constraint residual (reformulated as equalities with slacks.
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, SmartPtr< const IpoptData > ip_data, SmartPtr< IpoptCalculatedQuantities > ip_cq)=0
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)=0
Initialize (create) structures for the iteration data.
This is the abstract base class for classes that map the traditional NLP into something that is more ...
virtual SmartPtr< const Vector > x_L() const =0
Lower bounds on x.
virtual Index d_evals() const =0
virtual SmartPtr< const Vector > c(const Vector &x)=0
Equality constraint residual.
virtual Index jac_d_evals() const =0
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)=0
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)=0
Accessor method for vector/matrix spaces pointers.