#include <BranchAndBound.h>

Inheritance diagram for idol::BranchAndBound< NodeT >:

Collaboration diagram for idol::BranchAndBound< NodeT >:

Public Types
template<class ReturnT , class T >
using	only_if_has_Strategy = typename std::pair< typename T::template Strategy< NodeT >, ReturnT >::second_type

Public Member Functions
	BranchAndBound ()=default

	BranchAndBound (const BranchAndBound &t_rhs)

BranchAndBound< NodeT > &	with_node_optimizer (const OptimizerFactory &t_node_optimizer)

void	set_node_optimizer (const OptimizerFactory &t_node_optimizer)

BranchAndBound< NodeT > &	operator+= (const OptimizerFactory &t_node_optimizer)

BranchAndBound< NodeT > &	with_branching_rule (const BranchingRuleFactory< NodeT > &t_branching_rule)

template<class BranchingRuleFactoryT >
only_if_has_Strategy< BranchAndBound< NodeT > &, BranchingRuleFactoryT >	with_branching_rule (const BranchingRuleFactoryT &t_branching_rule)

BranchAndBound< NodeT > &	with_node_selection_rule (const NodeSelectionRuleFactory< NodeT > &t_node_selection)

template<class NodeSelectionRuleFactoryT >
only_if_has_Strategy< BranchAndBound< NodeT > &, NodeSelectionRuleFactoryT >	with_node_selection_rule (const NodeSelectionRuleFactoryT &t_node_selection_rule)

	BranchAndBound (BranchAndBound &&) noexcept=default

BranchAndBound &	operator= (const BranchAndBound &)=delete

BranchAndBound &	operator= (BranchAndBound &&) noexcept=delete

Optimizer *	operator() (const Model &t_model) const override

OptimizerFactory *	clone () const override

BranchAndBound< NodeT > &	with_subtree_depth (unsigned int t_depth)

BranchAndBound< NodeT > &	with_logger (const Logs::BranchAndBound::Factory< NodeT > &t_log_factory)

BranchAndBound< NodeT > &	add_callback (const BranchAndBoundCallbackFactory< NodeT > &t_callback)

BranchAndBound< NodeT > &	add_callback (const CallbackFactory &t_callback)

template<class NodeSelectionRuleFactoryT >
idol::BranchAndBound< NodeT >::template only_if_has_Strategy< idol::BranchAndBound< NodeT > &, NodeSelectionRuleFactoryT >	with_node_selection_rule (const NodeSelectionRuleFactoryT &t_node_selection_rule)

template<class BranchingRuleFactoryT >
idol::BranchAndBound< NodeT >::template only_if_has_Strategy< idol::BranchAndBound< NodeT > &, BranchingRuleFactoryT >	with_branching_rule (const BranchingRuleFactoryT &t_branching_rule)

CRTP &	with_logs (bool t_value)

CRTP &	with_time_limit (double t_time_limit)

CRTP &	with_thread_limit (unsigned int t_max_n_threads)

CRTP &	with_iteration_limit (unsigned int t_iteration_count_limit)

CRTP &	with_best_bound_stop (double t_best_bound_stop)

CRTP &	with_best_obj_stop (double t_user_best_obj)

CRTP &	with_relative_gap_tolerance (double t_relative_gap_tolerance)

CRTP &	with_absolute_gap_tolerance (double t_absolute_gap_tolerance)

CRTP &	with_presolve (bool t_value)

CRTP &	with_infeasible_or_unbounded_info (bool t_value)

CRTP &	conditional (bool t_conditional_value, const std::function< void(CRTP &)> &t_if)

CRTP &	conditional (bool t_conditional_value, const std::function< void(CRTP &)> &t_if, const std::function< void(CRTP &)> &t_else)

template<class T >
T &	as ()

template<class T >
const T &	as () const

template<class T >
bool	is () const

Protected Member Functions
CRTP &	crtp ()

const CRTP &	crtp () const

void	handle_default_parameters (Optimizer *t_optimizer) const

Detailed Description

template<class NodeT = idol::DefaultNodeInfo>
class idol::BranchAndBound< NodeT >

Template Parameters

NodeT the class used to store nodes information. It is strongly advised to inherit from NodeVarInfo in order to create your own node type.

Definition at line 29 of file BranchAndBound.h.

Member Typedef Documentation

◆ only_if_has_Strategy

template<class NodeT = idol::DefaultNodeInfo>

template<class ReturnT , class T >

using idol::BranchAndBound< NodeT >::only_if_has_Strategy = typename std::pair<typename T::template Strategy<NodeT>, ReturnT>::second_type

This type is used to exploit SFINAE in order to identify classes having a sub-class named Strategy<NodeInfoT>. This is used to make calls like .with_node_selection_rule(DepthFirst()); which will actually call .with_node_selection_rule(DepthFirst::Strategy<NodeInfoT>()).

Definition at line 46 of file BranchAndBound.h.

Constructor & Destructor Documentation

◆ BranchAndBound() [1/2]

template<class NodeT = idol::DefaultNodeInfo>

idol::BranchAndBound< NodeT >::BranchAndBound ( )

default

Creates a new branch-and-bound algorithm.

Example:

model.use( BranchAndBound() );

idol::BranchAndBound::BranchAndBound

BranchAndBound()=default

◆ BranchAndBound() [2/2]

template<class NodeT >

idol::BranchAndBound< NodeT >::BranchAndBound ( const BranchAndBound< NodeT > & t_rhs )

Copy constructor

Parameters

t_rhs the object to copy

Definition at line 310 of file BranchAndBound.h.

Member Function Documentation

◆ add_callback() [1/2]

template<class NodeT >

idol::BranchAndBound< NodeT > & idol::BranchAndBound< NodeT >::add_callback ( const BranchAndBoundCallbackFactory< NodeT > & t_callback )

Adds a callback which will be called by the optimizer.

Note that this method can be called multiple times so that multiple callbacks can be added.

auto algorithm = BranchAndBound()

.with_callback(IntegerMaster.rst());

Parameters

t_callback the callback factory

Returns: the optimizer factory itself

Definition at line 239 of file BranchAndBound.h.

◆ add_callback() [2/2]

template<class NodeT >

idol::BranchAndBound< NodeT > & idol::BranchAndBound< NodeT >::add_callback ( const CallbackFactory & t_callback )

Adds a (solver independent) callback which will be called by the optimizer.

Note that this method can be called multiple times so that multiple callbacks can be added.

Here, the Callback is automatically converted into a BranchAndBoundCallback<NodeInfoT>.

auto algorithm = BranchAndBound()

.with_callback(UserCutCallback(separation_model, my_cut));

idol::UserCutCallback

Definition UserCutCallback.h:15

Parameters

t_callback the callback factory

Returns: the optimizer factory itself

Definition at line 234 of file BranchAndBound.h.

◆ as() [1/2]

template<class T >

T & idol::OptimizerFactory::as ( )

inlineinherited

Definition at line 44 of file OptimizerFactory.h.

◆ as() [2/2]

template<class T >

const T & idol::OptimizerFactory::as ( ) const

inlineinherited

Definition at line 52 of file OptimizerFactory.h.

◆ clone()

template<class NodeT >

idol::OptimizerFactory * idol::BranchAndBound< NodeT >::clone ( ) const

overridevirtual

Creates and return a copy of the optimizer factory. This is used for polymorphism.

Returns: A copied object of the current object (i.e., *this)

Implements idol::OptimizerFactory.

Definition at line 366 of file BranchAndBound.h.

◆ conditional() [1/2]

template<class CRTP >

CRTP & idol::OptimizerFactoryWithDefaultParameters< CRTP >::conditional	(	bool	t_conditional_value,
		const std::function< void(CRTP &)> &	t_if
	)

inherited

Executes the lambda function given as second parameter if and only if its first argument is true. This function can be used to build different optimizer factories depending on some external variable.

Example:

for (const bool use_presolve : {true, false}) {
     auto algorithm = GLPK()
                         .conditional(use_presolve, [](auto& x){ x.with_presolve(true); })
      model.use(algorithm);
      model.optimize();
}

Parameters

t_conditional_value	if true, the t_if lambda function is executed, if false, nothing happens.
t_if	lambda function to execute in case t_conditional_value is true

Returns: the optimizer factory itself

Definition at line 273 of file OptimizerFactory.h.

◆ conditional() [2/2]

template<class CRTP >

CRTP & idol::OptimizerFactoryWithDefaultParameters< CRTP >::conditional	(	bool	t_conditional_value,
		const std::function< void(CRTP &)> &	t_if,
		const std::function< void(CRTP &)> &	t_else
	)

inherited

Executes the lambda function given as second parameter if and only if its first argument is true. This function can be used to build different optimizer factories depending on some external variable.

Example:

for (const bool use_presolve : {true, false}) {
     auto algorithm = GLPK()
                         .conditional(use_presolve,
                                         [](auto& x){ x.with_presolve(true); },
                                         [](auto& x){ x.with_presolve(false); })
      model.use(algorithm);
      model.optimize();
}

Parameters

t_conditional_value	if true, the t_if lambda function is executed, if false, the t_else lambda function is.
t_if	lambda function to execute in case t_conditional_value is true
t_else	lambda function to execute in case t_conditional_value is false

Returns: the optimizer factory itself

Definition at line 266 of file OptimizerFactory.h.

◆ crtp() [1/2]

template<class CRTP >

CRTP & idol::OptimizerFactoryWithDefaultParameters< CRTP >::crtp ( )

inlineprotectedinherited

Definition at line 78 of file OptimizerFactory.h.

◆ crtp() [2/2]

template<class CRTP >

const CRTP & idol::OptimizerFactoryWithDefaultParameters< CRTP >::crtp ( ) const

inlineprotectedinherited

Definition at line 79 of file OptimizerFactory.h.

◆ handle_default_parameters()

template<class CRTP >

void idol::OptimizerFactoryWithDefaultParameters< CRTP >::handle_default_parameters ( Optimizer * t_optimizer ) const

protectedinherited

Definition at line 398 of file OptimizerFactory.h.

◆ is()

template<class T >

bool idol::OptimizerFactory::is ( ) const

inlineinherited

Definition at line 60 of file OptimizerFactory.h.

◆ operator()()

template<class NodeT >

idol::Optimizer * idol::BranchAndBound< NodeT >::operator() ( const Model & t_model ) const

overridevirtual

Creates and returns a new optimizer to solve the model given as parameter.

Parameters

t_model The model which the optimizer will solve

Returns: A new optimizer for the model

Implements idol::OptimizerFactory.

Definition at line 326 of file BranchAndBound.h.

◆ operator+=()

template<class NodeT >

idol::BranchAndBound< NodeT > & idol::BranchAndBound< NodeT >::operator+= ( const OptimizerFactory & t_node_optimizer )

Definition at line 228 of file BranchAndBound.h.

◆ set_node_optimizer()

template<class NodeT >

void idol::BranchAndBound< NodeT >::set_node_optimizer ( const OptimizerFactory & t_node_optimizer )

Definition at line 210 of file BranchAndBound.h.

◆ with_absolute_gap_tolerance()

template<class CRTP >

CRTP & idol::OptimizerFactoryWithDefaultParameters< CRTP >::with_absolute_gap_tolerance ( double t_absolute_gap_tolerance )

inherited

Sets the absolute gap tolerance for the optimizer. When the optimizer proves that the absolute optimality gap is less than this threshold, the optimizer stops.

Example:

auto algorithm = GLPK()

.with_absolute_gap_tolerance(1e-4);

idol::OptimizerFactoryWithDefaultParameters::with_absolute_gap_tolerance

CRTP & with_absolute_gap_tolerance(double t_absolute_gap_tolerance)

Definition OptimizerFactory.h:302

Parameters

t_absolute_gap_tolerance the absolute gap tolerance

Returns: the optimizer factory itself

Definition at line 302 of file OptimizerFactory.h.

◆ with_best_bound_stop()

template<class CRTP >

CRTP & idol::OptimizerFactoryWithDefaultParameters< CRTP >::with_best_bound_stop ( double t_best_bound_stop )

inherited

Sets a threshold on the best bound for stopping the optimizer. When the optimizer have found a best bound which is greater than this threshold, the optimizer stops.

Example:

const double my_known_best_obj = 0.;
auto algorithm = GLPK()
                     .with_best_bound_stop(my_known_best_obj);

Parameters

t_best_bound_stop the threshold

Returns: the optimizer factory itself

Definition at line 338 of file OptimizerFactory.h.

◆ with_best_obj_stop()

template<class CRTP >

CRTP & idol::OptimizerFactoryWithDefaultParameters< CRTP >::with_best_obj_stop ( double t_user_best_obj )

inherited

Sets a threshold on the best objective value for stopping the optimizer. When the optimizer have found a best objective value which is less than this threshold, the optimizer stops.

Example:

const double my_known_best_bound = 0;
auto algorithm = GLPK()
                     .with_best_obj_stop(my_known_best_bound);

Parameters

t_user_best_obj the threshold

Returns: the optimizer factory itself

Definition at line 326 of file OptimizerFactory.h.

◆ with_branching_rule() [1/3]

template<class NodeT >

idol::BranchAndBound< NodeT > & idol::BranchAndBound< NodeT >::with_branching_rule ( const BranchingRuleFactory< NodeT > & t_branching_rule )

Sets the branching rule used to create child nodes

Example:

auto algorithm = BranchAndBound<NodeVarInfo>()

.with_branching_rule(MostInfeasible::Strategy<NodeVarInfo>());

idol::BranchAndBound

Definition BranchAndBound.h:29

idol::BranchAndBound::with_branching_rule

BranchAndBound< NodeT > & with_branching_rule(const BranchingRuleFactory< NodeT > &t_branching_rule)

Definition BranchAndBound.h:286

idol::MostInfeasible::Strategy

Definition MostInfeasible.h:23

Parameters

t_branching_rule the branching rule

Returns: the optimizer factory itself

Definition at line 286 of file BranchAndBound.h.

◆ with_branching_rule() [2/3]

template<class NodeT = idol::DefaultNodeInfo>

template<class BranchingRuleFactoryT >

only_if_has_Strategy< BranchAndBound< NodeT > &, BranchingRuleFactoryT > idol::BranchAndBound< NodeT >::with_branching_rule ( const BranchingRuleFactoryT & t_branching_rule )

Sets the branching rule used to create child nodes.

Here, the function is called only when BranchingRuleFactoryT has a nested template class named Strategy<NodeInfoT>. In such a case, the branching rule is created by calling BranchingRuleFactoryT::Strategy<NodeInfoT>(t_branching_rule). This is used to avoid the user repeating the node type NodeInfoT being used.

Example:

auto algorithm = BranchAndBound<NodeVarInfo>()

.with_branching_rule(MostInfeasible());

idol::MostInfeasible

Definition MostInfeasible.h:15

Template Parameters

BranchingRuleFactoryT the class containing a nested template class named Strategy

Parameters

t_branching_rule the branching rule

Returns: the optimizer factory itself

◆ with_branching_rule() [3/3]

template<class NodeT = idol::DefaultNodeInfo>

template<class BranchingRuleFactoryT >

idol::BranchAndBound< NodeT >::template only_if_has_Strategy< idol::BranchAndBound< NodeT > &, BranchingRuleFactoryT > idol::BranchAndBound< NodeT >::with_branching_rule ( const BranchingRuleFactoryT & t_branching_rule )

Definition at line 281 of file BranchAndBound.h.

◆ with_infeasible_or_unbounded_info()

template<class CRTP >

CRTP & idol::OptimizerFactoryWithDefaultParameters< CRTP >::with_infeasible_or_unbounded_info ( bool t_value )

inherited

Sets the behaviour of the optimizer when a model is shown to be infeasible or unbounded. When set to true, the optimizer is forced to prove feasibility or unboundedness by providing a certificate.

Example:

auto algorithm = GLPK()

.with_infeasible_or_unbounded_info(true);

idol::OptimizerFactoryWithDefaultParameters::with_infeasible_or_unbounded_info

CRTP & with_infeasible_or_unbounded_info(bool t_value)

Definition OptimizerFactory.h:278

Parameters

t_value the activation level

Returns: the optimizer factory itself

Definition at line 278 of file OptimizerFactory.h.

◆ with_iteration_limit()

template<class CRTP >

CRTP & idol::OptimizerFactoryWithDefaultParameters< CRTP >::with_iteration_limit ( unsigned int t_iteration_count_limit )

inherited

Sets the maximum number of iterations which the optimizer go through

Example:

auto algorithm = GLPK()

.with_iteration_limit(200);

idol::OptimizerFactoryWithDefaultParameters::with_iteration_limit

CRTP & with_iteration_limit(unsigned int t_iteration_count_limit)

Definition OptimizerFactory.h:350

Parameters

t_iteration_count_limit the maximum number of iterations

Returns: the optimizer factory itself

Definition at line 350 of file OptimizerFactory.h.

◆ with_logger()

template<class NodeT = idol::DefaultNodeInfo>

idol::BranchAndBound< NodeT > & idol::BranchAndBound< NodeT >::with_logger ( const Logs::BranchAndBound< NodeT >::Factory< NodeT > & t_log_factory )

Definition at line 216 of file BranchAndBound.h.

◆ with_logs()

template<class CRTP >

CRTP & idol::OptimizerFactoryWithDefaultParameters< CRTP >::with_logs ( bool t_value )

inherited

Sets the log_master level and color for the optimizer

Example:

auto algorithm = GLPK()

.with_logs(true);

idol::OptimizerFactoryWithDefaultParameters::with_logs

CRTP & with_logs(bool t_value)

Definition OptimizerFactory.h:386

Parameters

t_log_level	the log_master level
t_log_color	the output color

Returns: the optimizer factory itself

Definition at line 386 of file OptimizerFactory.h.

◆ with_node_optimizer()

template<class NodeT >

idol::BranchAndBound< NodeT > & idol::BranchAndBound< NodeT >::with_node_optimizer ( const OptimizerFactory & t_node_optimizer )

Sets the optimizer for solving each of the branch-and-bound tree nodes

Example:

auto algorithm = BranchAndBound()

.with_node_optimizer(GLPK::ContinuousRelaxation());

Parameters

t_node_optimizer the optimizer factory the node problems

Returns: the optimizer factory itself

Definition at line 298 of file BranchAndBound.h.

◆ with_node_selection_rule() [1/3]

template<class NodeT >

idol::BranchAndBound< NodeT > & idol::BranchAndBound< NodeT >::with_node_selection_rule ( const NodeSelectionRuleFactory< NodeT > & t_node_selection )

Sets the node selection rule to explore the branch and bound tree.

auto algorithm = BranchAndBound<NodeVarInfo>()

.with_node_selection(BestBound::Strategy<NodeVarInfo>());

idol::BestBound::Strategy

Definition BestBound.h:18

Parameters

t_node_selection the node selection rule

Returns: the optimizer factory itself

Definition at line 267 of file BranchAndBound.h.

◆ with_node_selection_rule() [2/3]

template<class NodeT = idol::DefaultNodeInfo>

template<class NodeSelectionRuleFactoryT >

only_if_has_Strategy< BranchAndBound< NodeT > &, NodeSelectionRuleFactoryT > idol::BranchAndBound< NodeT >::with_node_selection_rule ( const NodeSelectionRuleFactoryT & t_node_selection_rule )

Sets the node selection rule to explore the branch and bound tree.

Here, the function is called only when NodeSelectionRuleFactoryT has a nested template class named Strategy<NodeInfoT>. In such a case, the node selection rule is created by calling NodeSelectionRuleFactoryT::Strategy<NodeInfoT>(t_node_selection_rule). This is used to avoid the user repeating the node type NodeInfoT being used.

Example:

auto algorithm = BranchAndBound<NodeVarInfo>()

.with_node_selection_rule(BestBound());

idol::BestBound

Definition BestBound.h:15

idol::BranchAndBound::with_node_selection_rule

BranchAndBound< NodeT > & with_node_selection_rule(const NodeSelectionRuleFactory< NodeT > &t_node_selection)

Definition BranchAndBound.h:267

Template Parameters

NodeSelectionRuleFactoryT the class containing a nested template class named Strategy

Parameters

t_node_selection_rule the node selection rule

Returns: the optimizer factory itself

◆ with_node_selection_rule() [3/3]

template<class NodeT = idol::DefaultNodeInfo>

template<class NodeSelectionRuleFactoryT >

idol::BranchAndBound< NodeT >::template only_if_has_Strategy< idol::BranchAndBound< NodeT > &, NodeSelectionRuleFactoryT > idol::BranchAndBound< NodeT >::with_node_selection_rule ( const NodeSelectionRuleFactoryT & t_node_selection_rule )

Definition at line 261 of file BranchAndBound.h.

◆ with_presolve()

template<class CRTP >

CRTP & idol::OptimizerFactoryWithDefaultParameters< CRTP >::with_presolve ( bool t_value )

inherited

Sets the get_param_presolve activation for the optimizer.

Example:

auto algorithm = GLPK()

.with_presolve(false); // turns off get_param_presolve phase

idol::OptimizerFactoryWithDefaultParameters::with_presolve

CRTP & with_presolve(bool t_value)

Definition OptimizerFactory.h:290

Parameters

t_value the activation level for the optimizer's get_param_presolve (0 for disabling, 1 for enabling)

Returns: the optimizer factory itself

Definition at line 290 of file OptimizerFactory.h.

◆ with_relative_gap_tolerance()

template<class CRTP >

CRTP & idol::OptimizerFactoryWithDefaultParameters< CRTP >::with_relative_gap_tolerance ( double t_relative_gap_tolerance )

inherited

Sets the relative gap tolerance for the optimizer. When the optimizer proves that the relative optimality gap is less than this threshold, the optimizer stops.

Example:

auto algorithm = GLPK()

.with_relative_gap_tolerance(.05); // sets a gap tolerance of 5%

idol::OptimizerFactoryWithDefaultParameters::with_relative_gap_tolerance

CRTP & with_relative_gap_tolerance(double t_relative_gap_tolerance)

Definition OptimizerFactory.h:314

Parameters

t_relative_gap_tolerance the relative gap tolerance

Returns: the optimizer factory itself

Definition at line 314 of file OptimizerFactory.h.

◆ with_subtree_depth()

template<class NodeT >

idol::BranchAndBound< NodeT > & idol::BranchAndBound< NodeT >::with_subtree_depth ( unsigned int t_depth )

Sets the depth for sub-tree exploration.

When a node is selected for branching, each of its children is explored. This exploration takes the form of a sub-tree exploration. When this parameter is set to 0, only the root node of this sub-tree is solved. Thus every child node are solved and the branch-and-bound algorithm is continued.

For strictly greater values of this parameter, the sub-tree is explored with a maximum depth equal to the value of this parameter.

For example, with a value of 1, each child node is solved along with its child nodes.

Example:

auto algorithm = BranchAndBound()

.with_subtree_depth(1);

Parameters

t_depth the maximum sub-tree exploration depth

Returns: the optimizer factory itself

Definition at line 247 of file BranchAndBound.h.

◆ with_thread_limit()

template<class CRTP >

CRTP & idol::OptimizerFactoryWithDefaultParameters< CRTP >::with_thread_limit ( unsigned int t_max_n_threads )

inherited

Sets the maximum number of threads which the optimizer can use

Example:

auto algorithm = GLPK()

.with_thread_limit(5);

idol::OptimizerFactoryWithDefaultParameters::with_thread_limit

CRTP & with_thread_limit(unsigned int t_max_n_threads)

Definition OptimizerFactory.h:362

Parameters

t_max_n_threads the number of threads which can be used

Returns: the optimizer factory itself

Definition at line 362 of file OptimizerFactory.h.

◆ with_time_limit()

template<class CRTP >

CRTP & idol::OptimizerFactoryWithDefaultParameters< CRTP >::with_time_limit ( double t_time_limit )

inherited

Sets the time limit for the optimizer

Example:

auto algorithm = GLPK()

.with_time_limit(3600);

idol::OptimizerFactoryWithDefaultParameters::with_time_limit

CRTP & with_time_limit(double t_time_limit)

Definition OptimizerFactory.h:374

Parameters

t_time_limit the time limit (in seconds)

Returns: the optimizer factory itself

Definition at line 374 of file OptimizerFactory.h.

Public Types

Public Member Functions

Protected Member Functions

Detailed Description

Member Typedef Documentation

◆ only_if_has_Strategy

Constructor & Destructor Documentation

◆ BranchAndBound() [1/2]

◆ BranchAndBound() [2/2]

Member Function Documentation

◆ add_callback() [1/2]

◆ add_callback() [2/2]

◆ as() [1/2]

◆ as() [2/2]

◆ clone()

◆ conditional() [1/2]

◆ conditional() [2/2]

◆ crtp() [1/2]

◆ crtp() [2/2]

◆ handle_default_parameters()

◆ is()

◆ operator()()

◆ operator+=()

◆ set_node_optimizer()

◆ with_absolute_gap_tolerance()

◆ with_best_bound_stop()

◆ with_best_obj_stop()

◆ with_branching_rule() [1/3]

◆ with_branching_rule() [2/3]

◆ with_branching_rule() [3/3]

◆ with_infeasible_or_unbounded_info()

◆ with_iteration_limit()

◆ with_logger()

◆ with_logs()

◆ with_node_optimizer()

◆ with_node_selection_rule() [1/3]

◆ with_node_selection_rule() [2/3]

◆ with_node_selection_rule() [3/3]

◆ with_presolve()

◆ with_relative_gap_tolerance()

◆ with_subtree_depth()

◆ with_thread_limit()

◆ with_time_limit()