#include <BonTMINLP2TNLP.hpp>
Inheritance diagram for Bonmin::TMINLP2TNLP:
Public Member Functions | |
void | outputDiffs (const std::string &probName, const std::string *varNames) |
Procedure to ouptut relevant informations to reproduce a sub-problem. | |
virtual bool | hasUpperBoundingObjective () |
Say if has a specific function to compute upper bounds. | |
double | evaluateUpperBoundingFunction (const double *x) |
Evaluate the upper bounding function at given point and store the result. | |
Constructors/Destructors | |
TMINLP2TNLP (const SmartPtr< TMINLP > tminlp) | |
TMINLP2TNLP (const TMINLP2TNLP &) | |
Copy Constructor. | |
virtual TMINLP2TNLP * | clone () const |
virtual copy . | |
virtual | ~TMINLP2TNLP () |
Default destructor. | |
Methods to modify the MINLP and form the NLP | |
Index | num_variables () const |
Get the number of variables. | |
Index | num_constraints () const |
Get the number of constraints. | |
Index | nnz_h_lag () |
Get the nomber of nz in hessian. | |
const TMINLP::VariableType * | var_types () |
Get the variable types. | |
const Number * | x_l () |
Get the current values for the lower bounds. | |
const Number * | x_u () |
Get the current values for the upper bounds. | |
const Number * | orig_x_l () const |
Get the original values for the lower bounds. | |
const Number * | orig_x_u () const |
Get the original values for the upper bounds. | |
const Number * | g_l () |
Get the current values for constraints lower bounds. | |
const Number * | g_u () |
Get the current values for constraints upper bounds. | |
const Number * | x_init () const |
get the starting primal point | |
const Number * | x_init_user () const |
get the user provided starting primal point | |
const Number * | duals_init () const |
get the starting dual point | |
const Number * | x_sol () const |
get the solution values | |
const Number * | g_sol () const |
get the g solution (activities) | |
const Number * | duals_sol () const |
get the dual values | |
SolverReturn | optimization_status () const |
Get Optimization status. | |
Number | obj_value () const |
Get the objective value. | |
void | set_obj_value (Number value) |
Manually set objective value. | |
void | force_fractionnal_sol () |
force solution to be fractionnal. | |
void | SetVariablesBounds (Index n, const Number *x_l, const Number *x_u) |
Change the bounds on the variables. | |
void | SetVariablesLowerBounds (Index n, const Number *x_l) |
Change the lower bound on the variables. | |
void | SetVariablesUpperBounds (Index n, const Number *x_u) |
Change the upper bound on the variable. | |
void | SetVariableBounds (Index var_no, Number x_l, Number x_u) |
Change the bounds on the variable. | |
void | SetVariableLowerBound (Index var_no, Number x_l) |
Change the lower bound on the variable. | |
void | SetVariableUpperBound (Index var_no, Number x_u) |
Change the upper bound on the variable. | |
void | SetStartingPoint (Index n, const Number *x_init) |
Change the starting point. | |
void | resetStartingPoint () |
reset the starting point to original one. | |
void | setxInit (Index ind, const Number val) |
Set component ind of the starting point. | |
void | setxInit (Index n, const Number *x_init) |
set the starting point to x_init | |
void | setDualInit (Index ind, const Number val) |
Set component ind of the dual starting point. | |
void | setDualsInit (Index n, const Number *duals_init) |
set the dual starting point to duals_init | |
void | Set_x_sol (Index n, const Number *x_sol) |
Set the contiuous solution. | |
void | SetVariableType (Index n, TMINLP::VariableType type) |
Change the type of the variable. | |
methods to gather information about the NLP | |
virtual bool | get_nlp_info (Index &n, Index &m, Index &nnz_jac_g, Index &nnz_h_lag, TNLP::IndexStyleEnum &index_style) |
This call is just passed onto the TMINLP object. | |
virtual bool | get_bounds_info (Index n, Number *x_l, Number *x_u, Index m, Number *g_l, Number *g_u) |
The caller is allowed to modify the bounds, so this method returns the internal bounds information. | |
virtual bool | get_constraints_linearity (Index m, LinearityType *const_types) |
Returns the constraint linearity. | |
virtual bool | hasLinearObjective () |
returns true if objective is linear. | |
virtual bool | get_starting_point (Index n, bool init_x, Number *x, bool init_z, Number *z_L, Number *z_U, Index m, bool init_lambda, Number *lambda) |
Method called by Ipopt to get the starting point. | |
virtual bool | get_scaling_parameters (Number &obj_scaling, bool &use_x_scaling, Index n, Number *x_scaling, bool &use_g_scaling, Index m, Number *g_scaling) |
Method that returns scaling parameters. | |
virtual bool | get_warm_start_iterate (IteratesVector &warm_start_iterate) |
Methat that returns an Ipopt IteratesVector that has the starting point for all internal varibles. | |
virtual bool | eval_f (Index n, const Number *x, bool new_x, Number &obj_value) |
Returns the value of the objective function in x. | |
virtual bool | eval_grad_f (Index n, const Number *x, bool new_x, Number *grad_f) |
Returns the vector of the gradient of the objective w.r.t. | |
virtual bool | eval_g (Index n, const Number *x, bool new_x, Index m, Number *g) |
Returns the vector of constraint values in x. | |
virtual bool | eval_jac_g (Index n, const Number *x, bool new_x, Index m, Index nele_jac, Index *iRow, Index *jCol, Number *values) |
Returns the jacobian of the constraints. | |
virtual bool | eval_gi (Index n, const Number *x, bool new_x, Index i, Number &gi) |
compute the value of a single constraint | |
virtual bool | eval_grad_gi (Index n, const Number *x, bool new_x, Index i, Index &nele_grad_gi, Index *jCol, Number *values) |
compute the structure or values of the gradient for one constraint | |
virtual bool | eval_h (Index n, const Number *x, bool new_x, Number obj_factor, Index m, const Number *lambda, bool new_lambda, Index nele_hess, Index *iRow, Index *jCol, Number *values) |
Return the hessian of the lagrangian. | |
Solution Methods | |
virtual void | finalize_solution (SolverReturn status, Index n, const Number *x, const Number *z_L, const Number *z_U, Index m, const Number *g, const Number *lambda, Number obj_value, const IpoptData *ip_data, IpoptCalculatedQuantities *ip_cq) |
This method is called when the algorithm is complete so the TNLP can store/write the solution. | |
virtual bool | intermediate_callback (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) |
Intermediate Callback method for the user. | |
Methods for setting and getting the warm starter | |
void | SetWarmStarter (SmartPtr< IpoptInteriorWarmStarter > warm_starter) |
SmartPtr< IpoptInteriorWarmStarter > | GetWarmStarter () |
Cuts management. | |
virtual void | addCuts (unsigned int numberCuts, const OsiRowCut **cuts) |
Add some linear cuts to the problem formulation (not implemented yet in base class). | |
virtual void | addCuts (const OsiCuts &cuts) |
Add some cuts to the problem formulaiton (handles Quadratics). | |
virtual void | removeCuts (unsigned int number, const int *toRemove) |
Remove some cuts to the formulation. | |
Protected Member Functions | |
Index | nnz_h_lag () const |
Access number of entries in tminlp_ hessian. | |
Index | nnz_jac_g () const |
Access number of entries in tminlp_ hessian. | |
TNLP::IndexStyleEnum | index_style () const |
Acces index_style. | |
Protected Attributes | |
These should be modified in derived class to always maintain there corecteness. | |
They are directly queried by OsiTMINLPInterface without virtual function for speed. | |
vector< TMINLP::VariableType > | var_types_ |
Types of the variable (TMINLP::CONTINUOUS, TMINLP::INTEGER, TMINLP::BINARY). | |
vector< Number > | x_l_ |
Current lower bounds on variables. | |
vector< Number > | x_u_ |
Current upper bounds on variables. | |
vector< Number > | orig_x_l_ |
Original lower bounds on variables. | |
vector< Number > | orig_x_u_ |
Original upper bounds on variables. | |
vector< Number > | g_l_ |
Lower bounds on constraints values. | |
vector< Number > | g_u_ |
Upper bounds on constraints values. | |
vector< Number > | x_init_ |
Initial primal point. | |
Number * | duals_init_ |
Initial values for all dual multipliers (constraints then lower bounds then upper bounds). | |
vector< Number > | x_init_user_ |
User-provideed initial prmal point. | |
vector< Number > | x_sol_ |
Optimal solution. | |
vector< Number > | g_sol_ |
Activities of constraint g( x_sol_). | |
vector< Number > | duals_sol_ |
Dual multipliers of constraints and bounds. | |
Private Member Functions | |
void | throw_exception_on_bad_variable_bound (Index i) |
Private method that throws an exception if the variable bounds are not consistent with the variable type. | |
void | gutsOfDelete () |
void | gutsOfCopy (const TMINLP2TNLP &source) |
Copies all the arrays. | |
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. | |
TMINLP2TNLP () | |
Default Constructor. | |
TMINLP2TNLP & | operator= (const TMINLP2TNLP &) |
Overloaded Equals Operator. | |
Private Attributes | |
SmartPtr< TMINLP > | tminlp_ |
pointer to the tminlp that is being adapted | |
Internal copies of data allowing caller to modify the MINLP | |
Index | nnz_jac_g_ |
Number of non-zeroes in the constraints jacobian. | |
Index | nnz_h_lag_ |
Number of non-zeroes in the lagrangian hessian. | |
TNLP::IndexStyleEnum | index_style_ |
index style (fortran or C) | |
SolverReturn | return_status_ |
Return status of the optimization process. | |
Number | obj_value_ |
Value of the optimal solution found by Ipopt. | |
Warmstart object and related data | |
SmartPtr< IpoptInteriorWarmStarter > | curr_warm_starter_ |
Pointer to object that holds warmstart information. | |
Number | nlp_lower_bound_inf_ |
Value for a lower bound that denotes -infinity. | |
Number | nlp_upper_bound_inf_ |
Value for a upper bound that denotes infinity. | |
bool | warm_start_entire_iterate_ |
Option from Ipopt - we currently use it to see if we want to use some clever warm start or just the last iterate from the previous run. | |
bool | need_new_warm_starter_ |
Do we need a new warm starter object. |
It allows an external caller to modify the bounds of variables, allowing the treatment of binary and integer variables as relaxed, or fixed
Definition at line 32 of file BonTMINLP2TNLP.hpp.
Bonmin::TMINLP2TNLP::TMINLP2TNLP | ( | const TMINLP2TNLP & | ) |
Copy Constructor.
virtual Bonmin::TMINLP2TNLP::~TMINLP2TNLP | ( | ) | [virtual] |
Default destructor.
Bonmin::TMINLP2TNLP::TMINLP2TNLP | ( | ) | [private] |
virtual TMINLP2TNLP* Bonmin::TMINLP2TNLP::clone | ( | ) | const [inline, virtual] |
Index Bonmin::TMINLP2TNLP::num_variables | ( | ) | const [inline] |
Index Bonmin::TMINLP2TNLP::num_constraints | ( | ) | const [inline] |
Index Bonmin::TMINLP2TNLP::nnz_h_lag | ( | ) | [inline] |
Get the nomber of nz in hessian.
Definition at line 74 of file BonTMINLP2TNLP.hpp.
References nnz_h_lag_.
const TMINLP::VariableType* Bonmin::TMINLP2TNLP::var_types | ( | ) | [inline] |
const Number* Bonmin::TMINLP2TNLP::x_l | ( | ) | [inline] |
Get the current values for the lower bounds.
Definition at line 85 of file BonTMINLP2TNLP.hpp.
References x_l_.
const Number* Bonmin::TMINLP2TNLP::x_u | ( | ) | [inline] |
Get the current values for the upper bounds.
Definition at line 90 of file BonTMINLP2TNLP.hpp.
References x_u_.
const Number* Bonmin::TMINLP2TNLP::orig_x_l | ( | ) | const [inline] |
Get the original values for the lower bounds.
Definition at line 96 of file BonTMINLP2TNLP.hpp.
References orig_x_l_.
const Number* Bonmin::TMINLP2TNLP::orig_x_u | ( | ) | const [inline] |
Get the original values for the upper bounds.
Definition at line 101 of file BonTMINLP2TNLP.hpp.
References orig_x_u_.
const Number* Bonmin::TMINLP2TNLP::g_l | ( | ) | [inline] |
Get the current values for constraints lower bounds.
Definition at line 107 of file BonTMINLP2TNLP.hpp.
References g_l_.
const Number* Bonmin::TMINLP2TNLP::g_u | ( | ) | [inline] |
Get the current values for constraints upper bounds.
Definition at line 112 of file BonTMINLP2TNLP.hpp.
References g_u_.
const Number* Bonmin::TMINLP2TNLP::x_init | ( | ) | const [inline] |
get the starting primal point
Definition at line 118 of file BonTMINLP2TNLP.hpp.
References x_init_.
const Number* Bonmin::TMINLP2TNLP::x_init_user | ( | ) | const [inline] |
get the user provided starting primal point
Definition at line 124 of file BonTMINLP2TNLP.hpp.
References x_init_user_.
const Number* Bonmin::TMINLP2TNLP::duals_init | ( | ) | const [inline] |
get the starting dual point
Definition at line 130 of file BonTMINLP2TNLP.hpp.
References duals_init_.
const Number* Bonmin::TMINLP2TNLP::x_sol | ( | ) | const [inline] |
const Number* Bonmin::TMINLP2TNLP::g_sol | ( | ) | const [inline] |
get the g solution (activities)
Definition at line 142 of file BonTMINLP2TNLP.hpp.
References g_sol_.
const Number* Bonmin::TMINLP2TNLP::duals_sol | ( | ) | const [inline] |
SolverReturn Bonmin::TMINLP2TNLP::optimization_status | ( | ) | const [inline] |
Get Optimization status.
Definition at line 154 of file BonTMINLP2TNLP.hpp.
References return_status_.
Number Bonmin::TMINLP2TNLP::obj_value | ( | ) | const [inline] |
void Bonmin::TMINLP2TNLP::set_obj_value | ( | Number | value | ) | [inline] |
Manually set objective value.
Definition at line 166 of file BonTMINLP2TNLP.hpp.
References obj_value_.
void Bonmin::TMINLP2TNLP::force_fractionnal_sol | ( | ) |
force solution to be fractionnal.
Change the bounds on the variables.
Change the lower bound on the variables.
Change the upper bound on the variable.
Change the bounds on the variable.
Change the lower bound on the variable.
Change the upper bound on the variable.
Change the starting point.
void Bonmin::TMINLP2TNLP::resetStartingPoint | ( | ) |
reset the starting point to original one.
Set component ind of the starting point.
set the starting point to x_init
Set component ind of the dual starting point.
set the dual starting point to duals_init
void Bonmin::TMINLP2TNLP::SetVariableType | ( | Index | n, | |
TMINLP::VariableType | type | |||
) |
Change the type of the variable.
void Bonmin::TMINLP2TNLP::outputDiffs | ( | const std::string & | probName, | |
const std::string * | varNames | |||
) |
Procedure to ouptut relevant informations to reproduce a sub-problem.
Compare the current problem to the problem to solve and writes files with bounds which have changed and current starting point.
virtual bool Bonmin::TMINLP2TNLP::get_nlp_info | ( | Index & | n, | |
Index & | m, | |||
Index & | nnz_jac_g, | |||
Index & | nnz_h_lag, | |||
TNLP::IndexStyleEnum & | index_style | |||
) | [virtual] |
virtual bool Bonmin::TMINLP2TNLP::get_bounds_info | ( | Index | n, | |
Number * | x_l, | |||
Number * | x_u, | |||
Index | m, | |||
Number * | g_l, | |||
Number * | g_u | |||
) | [virtual] |
The caller is allowed to modify the bounds, so this method returns the internal bounds information.
Implements Ipopt::TNLP.
virtual bool Bonmin::TMINLP2TNLP::get_constraints_linearity | ( | Index | m, | |
LinearityType * | const_types | |||
) | [inline, virtual] |
Returns the constraint linearity.
array should be alocated with length at least n. (default implementation just return false and does not fill the array).
Definition at line 243 of file BonTMINLP2TNLP.hpp.
References tminlp_.
virtual bool Bonmin::TMINLP2TNLP::hasLinearObjective | ( | ) | [inline, virtual] |
returns true if objective is linear.
Definition at line 249 of file BonTMINLP2TNLP.hpp.
References tminlp_.
virtual bool Bonmin::TMINLP2TNLP::get_starting_point | ( | Index | n, | |
bool | init_x, | |||
Number * | x, | |||
bool | init_z, | |||
Number * | z_L, | |||
Number * | z_U, | |||
Index | m, | |||
bool | init_lambda, | |||
Number * | lambda | |||
) | [virtual] |
Method called by Ipopt to get the starting point.
The bools init_x and init_lambda are both inputs and outputs. As inputs, they indicate whether or not the algorithm wants you to initialize x and lambda respectively. If, for some reason, the algorithm wants you to initialize these and you cannot, set the respective bool to false.
Implements Ipopt::TNLP.
virtual bool Bonmin::TMINLP2TNLP::get_warm_start_iterate | ( | IteratesVector & | warm_start_iterate | ) | [virtual] |
Methat that returns an Ipopt IteratesVector that has the starting point for all internal varibles.
Reimplemented from Ipopt::TNLP.
virtual bool Bonmin::TMINLP2TNLP::eval_jac_g | ( | Index | n, | |
const Number * | x, | |||
bool | new_x, | |||
Index | m, | |||
Index | nele_jac, | |||
Index * | iRow, | |||
Index * | jCol, | |||
Number * | values | |||
) | [virtual] |
Returns the jacobian of the constraints.
The vectors iRow and jCol only need to be set once. The first call is used to set the structure only (iRow and jCol will be non-NULL, and values will be NULL) For subsequent calls, iRow and jCol will be NULL.
Implements Ipopt::TNLP.
virtual bool Bonmin::TMINLP2TNLP::eval_gi | ( | Index | n, | |
const Number * | x, | |||
bool | new_x, | |||
Index | i, | |||
Number & | gi | |||
) | [virtual] |
compute the value of a single constraint
virtual bool Bonmin::TMINLP2TNLP::eval_grad_gi | ( | Index | n, | |
const Number * | x, | |||
bool | new_x, | |||
Index | i, | |||
Index & | nele_grad_gi, | |||
Index * | jCol, | |||
Number * | values | |||
) | [virtual] |
compute the structure or values of the gradient for one constraint
virtual bool Bonmin::TMINLP2TNLP::eval_h | ( | Index | n, | |
const Number * | x, | |||
bool | new_x, | |||
Number | obj_factor, | |||
Index | m, | |||
const Number * | lambda, | |||
bool | new_lambda, | |||
Index | nele_hess, | |||
Index * | iRow, | |||
Index * | jCol, | |||
Number * | values | |||
) | [virtual] |
Return the hessian of the lagrangian.
The vectors iRow and jCol only need to be set once (during the first call). The first call is used to set the structure only (iRow and jCol will be non-NULL, and values will be NULL) For subsequent calls, iRow and jCol will be NULL. This matrix is symmetric - specify the lower diagonal only
Reimplemented from Ipopt::TNLP.
virtual void Bonmin::TMINLP2TNLP::finalize_solution | ( | SolverReturn | status, | |
Index | n, | |||
const Number * | x, | |||
const Number * | z_L, | |||
const Number * | z_U, | |||
Index | m, | |||
const Number * | g, | |||
const Number * | lambda, | |||
Number | obj_value, | |||
const IpoptData * | ip_data, | |||
IpoptCalculatedQuantities * | ip_cq | |||
) | [virtual] |
This method is called when the algorithm is complete so the TNLP can store/write the solution.
virtual bool Bonmin::TMINLP2TNLP::intermediate_callback | ( | 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 | |||
) | [virtual] |
Intermediate Callback method for the user.
Providing dummy default implementation. For details see IntermediateCallBack in IpNLP.hpp.
Reimplemented from Ipopt::TNLP.
void Bonmin::TMINLP2TNLP::SetWarmStarter | ( | SmartPtr< IpoptInteriorWarmStarter > | warm_starter | ) |
SmartPtr<IpoptInteriorWarmStarter> Bonmin::TMINLP2TNLP::GetWarmStarter | ( | ) |
virtual bool Bonmin::TMINLP2TNLP::hasUpperBoundingObjective | ( | ) | [inline, virtual] |
Say if has a specific function to compute upper bounds.
Definition at line 354 of file BonTMINLP2TNLP.hpp.
References tminlp_.
double Bonmin::TMINLP2TNLP::evaluateUpperBoundingFunction | ( | const double * | x | ) |
Evaluate the upper bounding function at given point and store the result.
virtual void Bonmin::TMINLP2TNLP::addCuts | ( | unsigned int | numberCuts, | |
const OsiRowCut ** | cuts | |||
) | [inline, virtual] |
Add some linear cuts to the problem formulation (not implemented yet in base class).
Definition at line 366 of file BonTMINLP2TNLP.hpp.
virtual void Bonmin::TMINLP2TNLP::addCuts | ( | const OsiCuts & | cuts | ) | [inline, virtual] |
Add some cuts to the problem formulaiton (handles Quadratics).
Definition at line 372 of file BonTMINLP2TNLP.hpp.
References OsiCuts::sizeColCuts(), and OsiCuts::sizeRowCuts().
virtual void Bonmin::TMINLP2TNLP::removeCuts | ( | unsigned int | number, | |
const int * | toRemove | |||
) | [inline, virtual] |
Index Bonmin::TMINLP2TNLP::nnz_h_lag | ( | ) | const [inline, protected] |
Access number of entries in tminlp_ hessian.
Definition at line 417 of file BonTMINLP2TNLP.hpp.
References nnz_h_lag_.
Index Bonmin::TMINLP2TNLP::nnz_jac_g | ( | ) | const [inline, protected] |
Access number of entries in tminlp_ hessian.
Definition at line 420 of file BonTMINLP2TNLP.hpp.
References nnz_jac_g_.
TNLP::IndexStyleEnum Bonmin::TMINLP2TNLP::index_style | ( | ) | const [inline, protected] |
TMINLP2TNLP& Bonmin::TMINLP2TNLP::operator= | ( | const TMINLP2TNLP & | ) | [private] |
Overloaded Equals Operator.
void Bonmin::TMINLP2TNLP::throw_exception_on_bad_variable_bound | ( | Index | i | ) | [private] |
Private method that throws an exception if the variable bounds are not consistent with the variable type.
void Bonmin::TMINLP2TNLP::gutsOfDelete | ( | ) | [private] |
void Bonmin::TMINLP2TNLP::gutsOfCopy | ( | const TMINLP2TNLP & | source | ) | [private] |
Copies all the arrays.
AW: I am trying to mimic a copy construction for Cbc use with great care not safe.
vector<TMINLP::VariableType> Bonmin::TMINLP2TNLP::var_types_ [protected] |
Types of the variable (TMINLP::CONTINUOUS, TMINLP::INTEGER, TMINLP::BINARY).
Definition at line 389 of file BonTMINLP2TNLP.hpp.
Referenced by var_types().
vector<Number> Bonmin::TMINLP2TNLP::x_l_ [protected] |
Current lower bounds on variables.
Definition at line 391 of file BonTMINLP2TNLP.hpp.
Referenced by num_variables(), and x_l().
vector<Number> Bonmin::TMINLP2TNLP::x_u_ [protected] |
Current upper bounds on variables.
Definition at line 393 of file BonTMINLP2TNLP.hpp.
Referenced by num_variables(), and x_u().
vector<Number> Bonmin::TMINLP2TNLP::orig_x_l_ [protected] |
Original lower bounds on variables.
Definition at line 395 of file BonTMINLP2TNLP.hpp.
Referenced by orig_x_l().
vector<Number> Bonmin::TMINLP2TNLP::orig_x_u_ [protected] |
Original upper bounds on variables.
Definition at line 397 of file BonTMINLP2TNLP.hpp.
Referenced by orig_x_u().
vector<Number> Bonmin::TMINLP2TNLP::g_l_ [protected] |
Lower bounds on constraints values.
Definition at line 399 of file BonTMINLP2TNLP.hpp.
Referenced by g_l(), and num_constraints().
vector<Number> Bonmin::TMINLP2TNLP::g_u_ [protected] |
Upper bounds on constraints values.
Definition at line 401 of file BonTMINLP2TNLP.hpp.
Referenced by g_u(), and num_constraints().
vector<Number> Bonmin::TMINLP2TNLP::x_init_ [protected] |
Number* Bonmin::TMINLP2TNLP::duals_init_ [protected] |
Initial values for all dual multipliers (constraints then lower bounds then upper bounds).
Definition at line 405 of file BonTMINLP2TNLP.hpp.
Referenced by duals_init().
vector<Number> Bonmin::TMINLP2TNLP::x_init_user_ [protected] |
User-provideed initial prmal point.
Definition at line 407 of file BonTMINLP2TNLP.hpp.
Referenced by x_init_user().
vector<Number> Bonmin::TMINLP2TNLP::x_sol_ [protected] |
vector<Number> Bonmin::TMINLP2TNLP::g_sol_ [protected] |
Activities of constraint g( x_sol_).
Definition at line 411 of file BonTMINLP2TNLP.hpp.
Referenced by g_sol().
vector<Number> Bonmin::TMINLP2TNLP::duals_sol_ [protected] |
Dual multipliers of constraints and bounds.
Definition at line 413 of file BonTMINLP2TNLP.hpp.
Referenced by duals_sol().
SmartPtr<TMINLP> Bonmin::TMINLP2TNLP::tminlp_ [private] |
pointer to the tminlp that is being adapted
Definition at line 443 of file BonTMINLP2TNLP.hpp.
Referenced by get_constraints_linearity(), hasLinearObjective(), and hasUpperBoundingObjective().
Index Bonmin::TMINLP2TNLP::nnz_jac_g_ [private] |
Number of non-zeroes in the constraints jacobian.
Definition at line 448 of file BonTMINLP2TNLP.hpp.
Referenced by nnz_jac_g().
Index Bonmin::TMINLP2TNLP::nnz_h_lag_ [private] |
Number of non-zeroes in the lagrangian hessian.
Definition at line 450 of file BonTMINLP2TNLP.hpp.
Referenced by nnz_h_lag().
index style (fortran or C)
Definition at line 452 of file BonTMINLP2TNLP.hpp.
Referenced by index_style().
Return status of the optimization process.
Definition at line 455 of file BonTMINLP2TNLP.hpp.
Referenced by optimization_status().
Number Bonmin::TMINLP2TNLP::obj_value_ [private] |
Value of the optimal solution found by Ipopt.
Definition at line 457 of file BonTMINLP2TNLP.hpp.
Referenced by obj_value(), and set_obj_value().
Pointer to object that holds warmstart information.
Definition at line 463 of file BonTMINLP2TNLP.hpp.
bool Bonmin::TMINLP2TNLP::warm_start_entire_iterate_ [private] |
Option from Ipopt - we currently use it to see if we want to use some clever warm start or just the last iterate from the previous run.
Definition at line 471 of file BonTMINLP2TNLP.hpp.
bool Bonmin::TMINLP2TNLP::need_new_warm_starter_ [private] |