This is an adapter class that converts a TMINLP to a TNLP to be solved by Ipopt. More...

#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.
virtual const int *	get_const_xtra_id () const
	Access array describing constraint to which perspectives should be applied.
double	check_solution (OsiObject **objects=0, int nObjects=-1)
	Round and check the current solution, return norm inf of constraint violation.
Constructors/Destructors
	TMINLP2TNLP (const Ipopt::SmartPtr< TMINLP > tminlp)
	Copy Constructor.
	TMINLP2TNLP (const TMINLP2TNLP &)
	Copy Constructor.
virtual TMINLP2TNLP *	clone () const
	virtual copy .
virtual	~TMINLP2TNLP ()
	Default destructor.
Methods to modify the MINLP and form the NLP
Ipopt::Index	num_variables () const
	Get the number of variables.
Ipopt::Index	num_constraints () const
	Get the number of constraints.
Ipopt::Index	nnz_h_lag ()
	Get the nomber of nz in hessian.
const TMINLP::VariableType *	var_types ()
	Get the variable types.
const Ipopt::Number *	x_l ()
	Get the current values for the lower bounds.
const Ipopt::Number *	x_u ()
	Get the current values for the upper bounds.
const Ipopt::Number *	orig_x_l () const
	Get the original values for the lower bounds.
const Ipopt::Number *	orig_x_u () const
	Get the original values for the upper bounds.
const Ipopt::Number *	g_l ()
	Get the current values for constraints lower bounds.
const Ipopt::Number *	g_u ()
	Get the current values for constraints upper bounds.
const Ipopt::Number *	x_init () const
	get the starting primal point
const Ipopt::Number *	x_init_user () const
	get the user provided starting primal point
const Ipopt::Number *	duals_init () const
	get the starting dual point
const Ipopt::Number *	x_sol () const
	get the solution values
const Ipopt::Number *	g_sol () const
	get the g solution (activities)
const Ipopt::Number *	duals_sol () const
	get the dual values
Ipopt::SolverReturn	optimization_status () const
	Get Optimization status.
Ipopt::Number	obj_value () const
	Get the objective value.
void	set_obj_value (Ipopt::Number value)
	Manually set objective value.
void	force_fractionnal_sol ()
	force solution to be fractionnal.
void	SetVariablesBounds (Ipopt::Index n, const Ipopt::Number x_l, const Ipopt::Number x_u)
	Change the bounds on the variables.
void	SetVariablesLowerBounds (Ipopt::Index n, const Ipopt::Number *x_l)
	Change the lower bound on the variables.
void	SetVariablesUpperBounds (Ipopt::Index n, const Ipopt::Number *x_u)
	Change the upper bound on the variable.
void	SetVariableBounds (Ipopt::Index var_no, Ipopt::Number x_l, Ipopt::Number x_u)
	Change the bounds on the variable.
void	SetVariableLowerBound (Ipopt::Index var_no, Ipopt::Number x_l)
	Change the lower bound on the variable.
void	SetVariableUpperBound (Ipopt::Index var_no, Ipopt::Number x_u)
	Change the upper bound on the variable.
void	resetStartingPoint ()
	reset the starting point to original one.
void	setxInit (Ipopt::Index n, const Ipopt::Number *x_init)
	set the starting point to x_init
void	setDualsInit (Ipopt::Index n, const Ipopt::Number *duals_init)
	set the dual starting point to duals_init
int	has_x_init ()
	xInit has been set?
void	Set_x_sol (Ipopt::Index n, const Ipopt::Number *x_sol)
	Set the contiuous solution.
void	Set_dual_sol (Ipopt::Index n, const Ipopt::Number *dual_sol)
	Set the contiuous dual solution.
void	SetVariableType (Ipopt::Index n, TMINLP::VariableType type)
	Change the type of the variable.
methods to gather information about the NLP
virtual bool	get_nlp_info (Ipopt::Index &n, Ipopt::Index &m, Ipopt::Index &nnz_jac_g, Ipopt::Index &nnz_h_lag, TNLP::IndexStyleEnum &index_style)
	This call is just passed onto the TMINLP object.
virtual bool	get_bounds_info (Ipopt::Index n, Ipopt::Number x_l, Ipopt::Number x_u, Ipopt::Index m, Ipopt::Number g_l, Ipopt::Number g_u)
	The caller is allowed to modify the bounds, so this method returns the internal bounds information.
virtual bool	get_constraints_linearity (Ipopt::Index m, LinearityType *const_types)
	Returns the constraint linearity.
virtual bool	get_variables_linearity (Ipopt::Index n, LinearityType *var_types)
	Returns the variables linearity.
virtual bool	hasLinearObjective ()
	returns true if objective is linear.
virtual bool	get_starting_point (Ipopt::Index n, bool init_x, Ipopt::Number x, bool init_z, Ipopt::Number z_L, Ipopt::Number z_U, Ipopt::Index m, bool init_lambda, Ipopt::Number lambda)
	Method called by Ipopt to get the starting point.
virtual bool	get_scaling_parameters (Ipopt::Number &obj_scaling, bool &use_x_scaling, Ipopt::Index n, Ipopt::Number x_scaling, bool &use_g_scaling, Ipopt::Index m, Ipopt::Number g_scaling)
	Method that returns scaling parameters.
virtual bool	get_warm_start_iterate (Ipopt::IteratesVector &warm_start_iterate)
	Methat that returns an Ipopt IteratesVector that has the starting point for all internal varibles.
virtual bool	eval_f (Ipopt::Index n, const Ipopt::Number *x, bool new_x, Ipopt::Number &obj_value)
	Returns the value of the objective function in x.
virtual bool	eval_grad_f (Ipopt::Index n, const Ipopt::Number x, bool new_x, Ipopt::Number grad_f)
	Returns the vector of the gradient of the objective w.r.t.
virtual bool	eval_g (Ipopt::Index n, const Ipopt::Number x, bool new_x, Ipopt::Index m, Ipopt::Number g)
	Returns the vector of constraint values in x.
virtual bool	eval_jac_g (Ipopt::Index n, const Ipopt::Number x, bool new_x, Ipopt::Index m, Ipopt::Index nele_jac, Ipopt::Index iRow, Ipopt::Index jCol, Ipopt::Number values)
	Returns the jacobian of the constraints.
virtual bool	eval_gi (Ipopt::Index n, const Ipopt::Number *x, bool new_x, Ipopt::Index i, Ipopt::Number &gi)
	compute the value of a single constraint
virtual bool	eval_grad_gi (Ipopt::Index n, const Ipopt::Number x, bool new_x, Ipopt::Index i, Ipopt::Index &nele_grad_gi, Ipopt::Index jCol, Ipopt::Number *values)
	compute the structure or values of the gradient for one constraint
virtual bool	eval_h (Ipopt::Index n, const Ipopt::Number x, bool new_x, Ipopt::Number obj_factor, Ipopt::Index m, const Ipopt::Number lambda, bool new_lambda, Ipopt::Index nele_hess, Ipopt::Index iRow, Ipopt::Index jCol, Ipopt::Number *values)
	Return the hessian of the lagrangian.
Solution Methods
virtual void	finalize_solution (Ipopt::SolverReturn status, Ipopt::Index n, const Ipopt::Number x, const Ipopt::Number z_L, const Ipopt::Number z_U, Ipopt::Index m, const Ipopt::Number g, const Ipopt::Number lambda, Ipopt::Number obj_value, const Ipopt::IpoptData ip_data, Ipopt::IpoptCalculatedQuantities *ip_cq)
	This method is called when the algorithm is complete so the TNLP can store/write the solution.
virtual bool	intermediate_callback (Ipopt::AlgorithmMode mode, Ipopt::Index iter, Ipopt::Number obj_value, Ipopt::Number inf_pr, Ipopt::Number inf_du, Ipopt::Number mu, Ipopt::Number d_norm, Ipopt::Number regularization_size, Ipopt::Number alpha_du, Ipopt::Number alpha_pr, Ipopt::Index ls_trials, const Ipopt::IpoptData ip_data, Ipopt::IpoptCalculatedQuantities ip_cq)
	Intermediate Callback method for the user.
Methods for setting and getting the warm starter
Method called to check wether a problem has still some variable not fixed. If there are no more unfixed vars, checks wether the solution given by the bounds is feasible.
void	SetWarmStarter (Ipopt::SmartPtr< IpoptInteriorWarmStarter > warm_starter)
Ipopt::SmartPtr < IpoptInteriorWarmStarter >	GetWarmStarter ()
Cuts management.
virtual void	addCuts (unsigned int numberCuts, const OsiRowCut **cuts)
	Methods are not implemented at this point.
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
Ipopt::Index	nnz_h_lag () const
	Access number of entries in tminlp_ hessian.
Ipopt::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< Ipopt::Number >	x_l_
	Current lower bounds on variables.
vector< Ipopt::Number >	x_u_
	Current upper bounds on variables.
vector< Ipopt::Number >	orig_x_l_
	Original lower bounds on variables.
vector< Ipopt::Number >	orig_x_u_
	Original upper bounds on variables.
vector< Ipopt::Number >	g_l_
	Lower bounds on constraints values.
vector< Ipopt::Number >	g_u_
	Upper bounds on constraints values.
vector< Ipopt::Number >	x_init_
	Initial primal point.
Ipopt::Number *	duals_init_
	Initial values for all dual multipliers (constraints then lower bounds then upper bounds)
vector< Ipopt::Number >	x_init_user_
	User-provideed initial prmal point.
vector< Ipopt::Number >	x_sol_
	Optimal solution.
vector< Ipopt::Number >	g_sol_
	Activities of constraint g( x_sol_)
vector< Ipopt::Number >	duals_sol_
	Dual multipliers of constraints and bounds.
Private Member Functions
void	throw_exception_on_bad_variable_bound (Ipopt::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
Ipopt::SmartPtr< TMINLP >	tminlp_
	pointer to the tminlp that is being adapted
Internal copies of data allowing caller to modify the MINLP
Ipopt::Index	nnz_jac_g_
	Number of non-zeroes in the constraints jacobian.
Ipopt::Index	nnz_h_lag_
	Number of non-zeroes in the lagrangian hessian.
TNLP::IndexStyleEnum	index_style_
	index style (fortran or C)
Ipopt::SolverReturn	return_status_
	Return status of the optimization process.
Ipopt::Number	obj_value_
	Value of the optimal solution found by Ipopt.
Warmstart object and related data
Ipopt::SmartPtr < IpoptInteriorWarmStarter >	curr_warm_starter_
	Pointer to object that holds warmstart information.
Ipopt::Number	nlp_lower_bound_inf_
	Value for a lower bound that denotes -infinity.
Ipopt::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.

Detailed Description

This is an adapter class that converts a TMINLP to a TNLP to be solved by Ipopt.

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.

Constructor & Destructor Documentation

Bonmin::TMINLP2TNLP::TMINLP2TNLP ( const Ipopt::SmartPtr< TMINLP > tminlp )

Copy Constructor.

Warning:: source and copy point to the same tminlp_.

Bonmin::TMINLP2TNLP::TMINLP2TNLP ( const TMINLP2TNLP & )

Copy Constructor.

Warning:: source and copy point to the same tminlp_.

virtual Bonmin::TMINLP2TNLP::~TMINLP2TNLP ( ) [virtual]

Default destructor.

Bonmin::TMINLP2TNLP::TMINLP2TNLP ( ) [private]

Default Constructor.

Referenced by clone().

Member Function Documentation

virtual TMINLP2TNLP* Bonmin::TMINLP2TNLP::clone ( ) const [inline, virtual]

virtual copy .

Reimplemented in Bonmin::TMINLP2TNLPQuadCuts.

Definition at line 50 of file BonTMINLP2TNLP.hpp.

References TMINLP2TNLP().

Ipopt::Index Bonmin::TMINLP2TNLP::num_variables ( ) const [inline]

Get the number of variables.

Definition at line 61 of file BonTMINLP2TNLP.hpp.

References x_l_, and x_u_.

Ipopt::Index Bonmin::TMINLP2TNLP::num_constraints ( ) const [inline]

Get the number of constraints.

Definition at line 68 of file BonTMINLP2TNLP.hpp.

References g_l_, and g_u_.

Ipopt::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]

Get the variable types.

Definition at line 79 of file BonTMINLP2TNLP.hpp.

References var_types_.

const Ipopt::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 Ipopt::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 Ipopt::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 Ipopt::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 Ipopt::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 Ipopt::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 Ipopt::Number* Bonmin::TMINLP2TNLP::x_init ( ) const [inline]

get the starting primal point

Definition at line 118 of file BonTMINLP2TNLP.hpp.

References x_init_.

const Ipopt::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 Ipopt::Number* Bonmin::TMINLP2TNLP::duals_init ( ) const [inline]

get the starting dual point

Definition at line 130 of file BonTMINLP2TNLP.hpp.

References duals_init_.

const Ipopt::Number* Bonmin::TMINLP2TNLP::x_sol ( ) const [inline]

get the solution values

Definition at line 136 of file BonTMINLP2TNLP.hpp.

References x_sol_.

const Ipopt::Number* Bonmin::TMINLP2TNLP::g_sol ( ) const [inline]

get the g solution (activities)

Definition at line 142 of file BonTMINLP2TNLP.hpp.

References g_sol_.

const Ipopt::Number* Bonmin::TMINLP2TNLP::duals_sol ( ) const [inline]

get the dual values

Definition at line 148 of file BonTMINLP2TNLP.hpp.

References duals_sol_.

Ipopt::SolverReturn Bonmin::TMINLP2TNLP::optimization_status ( ) const [inline]

Get Optimization status.

Definition at line 154 of file BonTMINLP2TNLP.hpp.

References return_status_.

Ipopt::Number Bonmin::TMINLP2TNLP::obj_value ( ) const [inline]

Get the objective value.

Definition at line 160 of file BonTMINLP2TNLP.hpp.

References obj_value_.

void Bonmin::TMINLP2TNLP::set_obj_value ( Ipopt::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.

void Bonmin::TMINLP2TNLP::SetVariablesBounds	(	Ipopt::Index	n,
		const Ipopt::Number *	x_l,
		const Ipopt::Number *	x_u
	)

Change the bounds on the variables.

void Bonmin::TMINLP2TNLP::SetVariablesLowerBounds	(	Ipopt::Index	n,
		const Ipopt::Number *	x_l
	)

Change the lower bound on the variables.

void Bonmin::TMINLP2TNLP::SetVariablesUpperBounds	(	Ipopt::Index	n,
		const Ipopt::Number *	x_u
	)

Change the upper bound on the variable.

void Bonmin::TMINLP2TNLP::SetVariableBounds	(	Ipopt::Index	var_no,
		Ipopt::Number	x_l,
		Ipopt::Number	x_u
	)

Change the bounds on the variable.

void Bonmin::TMINLP2TNLP::SetVariableLowerBound	(	Ipopt::Index	var_no,
		Ipopt::Number	x_l
	)

Change the lower bound on the variable.

void Bonmin::TMINLP2TNLP::SetVariableUpperBound	(	Ipopt::Index	var_no,
		Ipopt::Number	x_u
	)

Change the upper bound on the variable.

void Bonmin::TMINLP2TNLP::resetStartingPoint ( )

reset the starting point to original one.

void Bonmin::TMINLP2TNLP::setxInit	(	Ipopt::Index	n,
		const Ipopt::Number *	x_init
	)

set the starting point to x_init

void Bonmin::TMINLP2TNLP::setDualsInit	(	Ipopt::Index	n,
		const Ipopt::Number *	duals_init
	)

set the dual starting point to duals_init

int Bonmin::TMINLP2TNLP::has_x_init ( ) [inline]

xInit has been set?

Returns:: 0 if not, 1 if only primal 2 if primal dual.

Definition at line 207 of file BonTMINLP2TNLP.hpp.

References duals_init_, and x_init_.

void Bonmin::TMINLP2TNLP::Set_x_sol	(	Ipopt::Index	n,
		const Ipopt::Number *	x_sol
	)

Set the contiuous solution.

void Bonmin::TMINLP2TNLP::Set_dual_sol	(	Ipopt::Index	n,
		const Ipopt::Number *	dual_sol
	)

Set the contiuous dual solution.

void Bonmin::TMINLP2TNLP::SetVariableType	(	Ipopt::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	(	Ipopt::Index &	n,
		Ipopt::Index &	m,
		Ipopt::Index &	nnz_jac_g,
		Ipopt::Index &	nnz_h_lag,
		TNLP::IndexStyleEnum &	index_style
	)		`[virtual]`

This call is just passed onto the TMINLP object.

virtual bool Bonmin::TMINLP2TNLP::get_bounds_info	(	Ipopt::Index	n,
		Ipopt::Number *	x_l,
		Ipopt::Number *	x_u,
		Ipopt::Index	m,
		Ipopt::Number *	g_l,
		Ipopt::Number *	g_u
	)		`[virtual]`

The caller is allowed to modify the bounds, so this method returns the internal bounds information.

Reimplemented in Bonmin::TMINLP2TNLPQuadCuts.

virtual bool Bonmin::TMINLP2TNLP::get_constraints_linearity	(	Ipopt::Index	m,
		LinearityType *	const_types
	)		`[inline, virtual]`

Returns the constraint linearity.

array should be alocated with length at least m..

Definition at line 242 of file BonTMINLP2TNLP.hpp.

References tminlp_.

virtual bool Bonmin::TMINLP2TNLP::get_variables_linearity	(	Ipopt::Index	n,
		LinearityType *	var_types
	)		`[inline, virtual]`

Returns the variables linearity.

array should be alocated with length at least n..

Definition at line 249 of file BonTMINLP2TNLP.hpp.

References tminlp_.

virtual bool Bonmin::TMINLP2TNLP::hasLinearObjective ( ) [inline, virtual]

returns true if objective is linear.

Definition at line 255 of file BonTMINLP2TNLP.hpp.

References tminlp_.

virtual bool Bonmin::TMINLP2TNLP::get_starting_point	(	Ipopt::Index	n,
		bool	init_x,
		Ipopt::Number *	x,
		bool	init_z,
		Ipopt::Number *	z_L,
		Ipopt::Number *	z_U,
		Ipopt::Index	m,
		bool	init_lambda,
		Ipopt::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.

Reimplemented in Bonmin::TMINLP2TNLPQuadCuts.

virtual bool Bonmin::TMINLP2TNLP::get_scaling_parameters	(	Ipopt::Number &	obj_scaling,
		bool &	use_x_scaling,
		Ipopt::Index	n,
		Ipopt::Number *	x_scaling,
		bool &	use_g_scaling,
		Ipopt::Index	m,
		Ipopt::Number *	g_scaling
	)		`[virtual]`

Method that returns scaling parameters.

Reimplemented in Bonmin::TMINLP2TNLPQuadCuts.

virtual bool Bonmin::TMINLP2TNLP::get_warm_start_iterate ( Ipopt::IteratesVector & warm_start_iterate ) [virtual]

Methat that returns an Ipopt IteratesVector that has the starting point for all internal varibles.

virtual bool Bonmin::TMINLP2TNLP::eval_f	(	Ipopt::Index	n,
		const Ipopt::Number *	x,
		bool	new_x,
		Ipopt::Number &	obj_value
	)		`[virtual]`

Returns the value of the objective function in x.

Reimplemented in Bonmin::TMINLP2TNLPQuadCuts.

virtual bool Bonmin::TMINLP2TNLP::eval_grad_f	(	Ipopt::Index	n,
		const Ipopt::Number *	x,
		bool	new_x,
		Ipopt::Number *	grad_f
	)		`[virtual]`

Returns the vector of the gradient of the objective w.r.t.

x

Reimplemented in Bonmin::TMINLP2TNLPQuadCuts.

virtual bool Bonmin::TMINLP2TNLP::eval_g	(	Ipopt::Index	n,
		const Ipopt::Number *	x,
		bool	new_x,
		Ipopt::Index	m,
		Ipopt::Number *	g
	)		`[virtual]`

Returns the vector of constraint values in x.

Reimplemented in Bonmin::TMINLP2TNLPQuadCuts.

virtual bool Bonmin::TMINLP2TNLP::eval_jac_g	(	Ipopt::Index	n,
		const Ipopt::Number *	x,
		bool	new_x,
		Ipopt::Index	m,
		Ipopt::Index	nele_jac,
		Ipopt::Index *	iRow,
		Ipopt::Index *	jCol,
		Ipopt::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.

Reimplemented in Bonmin::TMINLP2TNLPQuadCuts.

virtual bool Bonmin::TMINLP2TNLP::eval_gi	(	Ipopt::Index	n,
		const Ipopt::Number *	x,
		bool	new_x,
		Ipopt::Index	i,
		Ipopt::Number &	gi
	)		`[virtual]`

compute the value of a single constraint

Reimplemented in Bonmin::TMINLP2TNLPQuadCuts.

virtual bool Bonmin::TMINLP2TNLP::eval_grad_gi	(	Ipopt::Index	n,
		const Ipopt::Number *	x,
		bool	new_x,
		Ipopt::Index	i,
		Ipopt::Index &	nele_grad_gi,
		Ipopt::Index *	jCol,
		Ipopt::Number *	values
	)		`[virtual]`

compute the structure or values of the gradient for one constraint

Reimplemented in Bonmin::TMINLP2TNLPQuadCuts.

virtual bool Bonmin::TMINLP2TNLP::eval_h	(	Ipopt::Index	n,
		const Ipopt::Number *	x,
		bool	new_x,
		Ipopt::Number	obj_factor,
		Ipopt::Index	m,
		const Ipopt::Number *	lambda,
		bool	new_lambda,
		Ipopt::Index	nele_hess,
		Ipopt::Index *	iRow,
		Ipopt::Index *	jCol,
		Ipopt::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 in Bonmin::TMINLP2TNLPQuadCuts.

virtual void Bonmin::TMINLP2TNLP::finalize_solution	(	Ipopt::SolverReturn	status,
		Ipopt::Index	n,
		const Ipopt::Number *	x,
		const Ipopt::Number *	z_L,
		const Ipopt::Number *	z_U,
		Ipopt::Index	m,
		const Ipopt::Number *	g,
		const Ipopt::Number *	lambda,
		Ipopt::Number	obj_value,
		const Ipopt::IpoptData *	ip_data,
		Ipopt::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	(	Ipopt::AlgorithmMode	mode,
		Ipopt::Index	iter,
		Ipopt::Number	obj_value,
		Ipopt::Number	inf_pr,
		Ipopt::Number	inf_du,
		Ipopt::Number	mu,
		Ipopt::Number	d_norm,
		Ipopt::Number	regularization_size,
		Ipopt::Number	alpha_du,
		Ipopt::Number	alpha_pr,
		Ipopt::Index	ls_trials,
		const Ipopt::IpoptData *	ip_data,
		Ipopt::IpoptCalculatedQuantities *	ip_cq
	)		`[virtual]`

Intermediate Callback method for the user.

Providing dummy default implementation. For details see IntermediateCallBack in IpNLP.hpp.

void Bonmin::TMINLP2TNLP::SetWarmStarter ( Ipopt::SmartPtr< IpoptInteriorWarmStarter > warm_starter )

Ipopt::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 360 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]`

Methods are not implemented at this point.

But I need the interface. Add some linear cuts to the problem formulation (not implemented yet in base class).

Reimplemented in Bonmin::TMINLP2TNLPQuadCuts.

Definition at line 372 of file BonTMINLP2TNLP.hpp.

virtual void Bonmin::TMINLP2TNLP::addCuts ( const OsiCuts & cuts ) [inline, virtual]

Add some cuts to the problem formulaiton (handles Quadratics).

Reimplemented in Bonmin::TMINLP2TNLPQuadCuts.

Definition at line 378 of file BonTMINLP2TNLP.hpp.

virtual void Bonmin::TMINLP2TNLP::removeCuts	(	unsigned int	number,
		const int *	toRemove
	)		`[inline, virtual]`

Remove some cuts to the formulation.

Reimplemented in Bonmin::TMINLP2TNLPQuadCuts.

Definition at line 383 of file BonTMINLP2TNLP.hpp.

virtual const int* Bonmin::TMINLP2TNLP::get_const_xtra_id ( ) const [inline, virtual]

Access array describing constraint to which perspectives should be applied.

Definition at line 391 of file BonTMINLP2TNLP.hpp.

References tminlp_.

double Bonmin::TMINLP2TNLP::check_solution	(	OsiObject **	objects = `0`,
		int	nObjects = `-1`
	)

Round and check the current solution, return norm inf of constraint violation.

Ipopt::Index Bonmin::TMINLP2TNLP::nnz_h_lag ( ) const [inline, protected]

Access number of entries in tminlp_ hessian.

Definition at line 431 of file BonTMINLP2TNLP.hpp.

References nnz_h_lag_.

Ipopt::Index Bonmin::TMINLP2TNLP::nnz_jac_g ( ) const [inline, protected]

Access number of entries in tminlp_ hessian.

Definition at line 434 of file BonTMINLP2TNLP.hpp.

References nnz_jac_g_.

TNLP::IndexStyleEnum Bonmin::TMINLP2TNLP::index_style ( ) const [inline, protected]

Acces index_style.

Definition at line 438 of file BonTMINLP2TNLP.hpp.

References index_style_.

TMINLP2TNLP& Bonmin::TMINLP2TNLP::operator= ( const TMINLP2TNLP & ) [private]

Overloaded Equals Operator.

Reimplemented in Bonmin::TMINLP2TNLPQuadCuts.

void Bonmin::TMINLP2TNLP::throw_exception_on_bad_variable_bound ( Ipopt::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.

Warning:: this and other should be two instances of the same problem; AW: I am trying to mimic a copy construction for Cbc use with great care not safe.