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# Sphinx build info version 1
# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
config: b32e9f9b54a993e9fb9309dea8d3d73d
tags: 645f666f9bcd5a90fca523b33c5a78b7
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31 changes: 31 additions & 0 deletions _sources/api/classes/branch-and-bound/BranchAndBound.rst.txt
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.. _api_BranchAndBound:

BranchAndBound
==============

This class is an optimizer factory which creates a new branch-and-bound algorithm.
It can be used to create customized branch-and-bound algorithms with a large degree of freedom.

.. seealso::

If you are not familiar with optimizers and optimizer factories, please refer to :ref:`this page <mip_optimizers>`.

.. admonition:: Example

Here, we create a simple branch-and-bound algorithm where branching is done on integer variables which are being
relaxed. Each node is solved by the external solver GLPK. Nodes are selected according to the "best-bound"
rule while variables are selected according to the "most-infeasible" branching rule.

The created algorithm also incorporates sub-tree exploration of maximum depth 2.

.. code-block::
model.use(
BranchAndBound()
.with_node_optimizer( GLPK::ContinuousRelaxation() )
.with_branching_rule( MostInfeasible() )
.with_node_selection_rule( BestBound() )
.with_subtree_depth(2)
);
.. doxygenclass:: idol::BranchAndBound
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.. _api_BranchAndBoundCallback:

BranchAndBoundCallback
======================

This class can be used to create callbacks to run on idol's :ref:`branch-and-bound implementation <api_BranchAndBound>`.

.. warning::

BranchAndBoundCallback-s is an *advanced* feature.

Please, make sure that what you are trying do cannot be done with
a :ref:`solver-independent callback <api_Callback>` first, or with pre-existing callbacks, e.g.,
:ref:`UserCutCallback <api_UserCutCallback>` or :ref:`LazyCutCallback <api_LazyCutCallback>`.

The advantage of using a :ref:`BranchAndBoundCallback <api_BranchAndBoundCallback>` instead of a standard
solver-independent :ref:`Callback <api_Callback>` lies in the possibility to access specific information regarding
the execution of the branch-and-bound algorithm. For instance, accessing a node's information, or the current
relaxation model being solved.

.. admonition:: Example

Here is an example of callback which prints out the event triggering it and, when the event corresponds to `NodeLoaded`,
prints the node's model to be solved.

.. code-block::
class MyCallback : public BranchAndBoundCallbackFactory<NodeInfo> {
public:
class Strategy : public BranchAndBoundCallback<NodeInfo> {
protected:
void operator()(CallbackEvent t_event) override {
std::cout << "MyCallback is called for " << t_event << std::endl;
if (t_event != NodeLoaded) {
return;
}
std::cout << "The problem being solve at node " << node().id() << std::endl;
std::cout << relaxation() << std::endl;
}
};
BranchAndBoundCallback<NodeInfo> *operator()() override {
return new Strategy();
}
[[nodiscard]] BranchAndBoundCallbackFactory<NodeInfo> *clone() const override {
return new MyCallback(*this);
}
};
Then, this callback can be used as follows.

.. code-block::
model.use(
BranchAndBound()
.with_node_optimizer(GLPK::ContinuousRelaxation())
.with_branching_rule(MostInfeasible())
.with_node_selection_rule(DepthFirst())
.with_callback(MyCallback());
);
.. hint::

By default, most of the objects returned by BranchAndBoundCallback methods are const. If you wish to access non-const
versions (e.g., if you want to perform non-standard updates to the relaxed model or want to change the node's current
information manually), you should use the advanced interface obtained by calling ``BranchAndBoundCallback::advanced_interface``.

.. doxygenclass:: idol::BranchAndBoundCallback
:protected-members:
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BranchAndBoundCallbackFactory
=============================

.. doxygenclass:: idol::BranchAndBoundCallbackFactory
:protected-members:
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Cuts::KnapsackCover
===================

.. doxygenclass:: idol::Cuts::KnapsackCover
10 changes: 10 additions & 0 deletions _sources/api/classes/branch-and-bound/cuts/index.rst.txt
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Cutting Planes
==============

.. toctree::
:maxdepth: 1
:glob:

*


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Heuristics::LocalBranching
==========================

.. doxygenclass:: idol::Heuristics::LocalBranching
4 changes: 4 additions & 0 deletions _sources/api/classes/branch-and-bound/heuristics/RENS.rst.txt
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Heuristics::RENS
================

.. doxygenclass:: idol::Heuristics::RENS
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Heuristics::SimpleRounding
==========================

.. doxygenclass:: idol::Heuristics::SimpleRounding
10 changes: 10 additions & 0 deletions _sources/api/classes/branch-and-bound/heuristics/index.rst.txt
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Heuristics
==========

.. toctree::
:maxdepth: 1
:glob:

*


12 changes: 12 additions & 0 deletions _sources/api/classes/branch-and-bound/index.rst.txt
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Branch-and-Bound Algorithm
==========================

.. toctree::
:maxdepth: 2
:glob:

*
variable-selection/index
node-selection/index
heuristics/index
cuts/index
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BestBound
=========

.. doxygenclass:: idol::BestBound
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BestEstimate
============

The "best estimate" node selection rule was introduced in *J. J. H. Forrest, J. P. H. Hirst, J. A. Tomlin, (1974) Practical Solution of Large Mixed Integer Programming Problems with Umpire. Management Science 20(5):736-773*.

.. doxygenclass:: idol::BestEstimate
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BreadthFirst
============

.. doxygenclass:: idol::BreadthFirst
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DepthFirst
==========

.. doxygenclass:: idol::DepthFirst
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WorstBound
==========

.. doxygenclass:: idol::WorstBound
10 changes: 10 additions & 0 deletions _sources/api/classes/branch-and-bound/node-selection/index.rst.txt
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Node Selection Rules
====================

.. toctree::
:maxdepth: 1
:glob:

*


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FirstInfeasibleFound
====================

.. doxygenclass:: idol::FirstInfeasibleFound
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LeastInfeasible
===============

.. doxygenclass:: idol::LeastInfeasible
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MostInfeasible
==============

.. doxygenclass:: idol::MostInfeasible
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PseudoCost
==========

.. doxygenclass:: idol::PseudoCost
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StrongBranching
===============

.. doxygenclass:: idol::StrongBranching
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UniformlyRandom
===============

.. doxygenclass:: idol::UniformlyRandom
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Branching Rules
===============

.. toctree::
:maxdepth: 1
:glob:

*


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.. _api_Robust_ColumnAndConstraintGeneration_doxygen:

Robust::ColumnAndConstraintGeneration
=====================================

.. doxygenclass:: idol::Robust::ColumnAndConstraintGeneration
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Optimizers::Robust::ColumnAndConstraintGeneration
=================================================

.. doxygenclass:: idol::Optimizers::Robust::ColumnAndConstraintGeneration
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Column-and-Constraint Generation Algorithm
==========================================

.. toctree::
:maxdepth: 1
:glob:

*
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DantzigWolfe::ArtificialCosts
=============================

.. doxygenclass:: idol::DantzigWolfe::ArtificialCosts
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DantzigWolfeDecomposition
=========================

.. hint::

This page documents on the `DantzigWolfeDecomposition` optimizer factory. Note that there are also
:ref:`Dantzig-Wolfe Decomposition tutorials <tutorial_DantzigWolfe>`.

.. doxygenclass:: idol::DantzigWolfeDecomposition
4 changes: 4 additions & 0 deletions _sources/api/classes/column-generation/FarkasPricing.rst.txt
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DantzigWolfe::FarkasPricing
===========================

.. doxygenclass:: idol::DantzigWolfe::FarkasPricing
9 changes: 9 additions & 0 deletions _sources/api/classes/column-generation/IntegerMaster.rst.txt
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Heuristics::IntegerMaster
=========================

.. warning::

This heuristic can only be used with a :code:`BranchAndBound<NodeVarInfo>` optimizer in which nodes are solved by
:code:`DantzigWolfeDecomposition`.

.. doxygenclass:: idol::Heuristics::IntegerMaster
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Optimizers::DantzigWolfeDecomposition
=====================================

.. doxygenclass:: idol::Optimizers::DantzigWolfeDecomposition
10 changes: 10 additions & 0 deletions _sources/api/classes/column-generation/index.rst.txt
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Column Generation Algorithm
===========================

.. toctree::
:maxdepth: 1
:glob:

*
stabilization/index

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DantzigWolfe::Neame
===================

.. doxygenclass:: idol::DantzigWolfe::Neame
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DantzigWolfe::Wentges
=====================

.. doxygenclass:: idol::DantzigWolfe::Wentges
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Stabilization
=============

.. toctree::
:maxdepth: 1
:glob:

*
27 changes: 27 additions & 0 deletions _sources/api/classes/common/Annotation.rst.txt
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Annotation
==========

Annotations are additional information associated to an optimization object (e.g., a constraint or a variable).
The Annotation class takes two template arguments: an optimization object type and a value type. For instance, we
can create an annotation for constraints of type :code:`unsigned int` as follows.

.. code:: cpp
Env env;
const unsigned int default_value = 0;
Annotation<Ctr, unsigned int> annotation(env, "my_annotation", default_value);
Note that annotations are global, i.e., they do not relate to a given optimization model and can, therefore, be accessed
anywhere in the code. Thus, given a constraint called :code:`constraint`, the value of the annotation can be accessed
by calling the :code:`Ctr::get` method.

.. code:: cpp
std::cout << "My annotation is " << constraint.get(annotation) << std::endl; // "0", i.e., the default_value value
Annotations are, in particular, used to give decomposition instructions to idol when designing a Branch-and-Price algorithm.
To learn more, check our `Branch-and-Price tutorials <tutorials_dantzig_wolfe>`_.

.. doxygenclass:: idol::Annotation
6 changes: 6 additions & 0 deletions _sources/api/classes/common/Column.rst.txt
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.. _api_Column:

Column
======

.. doxygenclass:: idol::Column
6 changes: 6 additions & 0 deletions _sources/api/classes/common/Constant.rst.txt
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.. _api_Constant:

Constant
========

.. doxygenclass:: idol::Constant
6 changes: 6 additions & 0 deletions _sources/api/classes/common/Ctr.rst.txt
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.. _api_Ctr:

Ctr
===

.. doxygenclass:: idol::Ctr
6 changes: 6 additions & 0 deletions _sources/api/classes/common/Env.rst.txt
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.. _api_Env:

Env
===

.. doxygenclass:: idol::Env
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