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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: 05230886c7594d5c2e517b68f35c2d81
tags: 645f666f9bcd5a90fca523b33c5a78b7
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11 changes: 11 additions & 0 deletions _sources/api/heuristics/IntegerMaster.rst.txt
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.. _api_Heuristics_IntegerMaster:

IntegerMaster
=============

.. warning::

This heuristic can only be used with a BranchAndBound optimizer in which nodes are solved by ColumnGeneration
or DantigWolfeReformulation.

.. doxygenclass:: idol::Heuristics::IntegerMaster
6 changes: 6 additions & 0 deletions _sources/api/heuristics/SimpleRounding.rst.txt
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.. _api_Heuristics_SimpleRounding:

SimpleRounding
==============

.. doxygenclass:: idol::Heuristics::SimpleRounding
11 changes: 11 additions & 0 deletions _sources/api/heuristics/index.rst.txt
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.. _heuristics:

Heuristics
==========

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

SimpleRounding
IntegerMaster
14 changes: 14 additions & 0 deletions _sources/api/index.rst.txt
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.. _api:

API
===

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

modeling/index
optimizers/index
heuristics/index
problems/index
tolerances
4 changes: 4 additions & 0 deletions _sources/api/modeling/Annotation.rst.txt
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Annotation
==========

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

Column
======

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

Constant
========

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

Ctr
===

.. doxygenclass:: idol::Ctr
4 changes: 4 additions & 0 deletions _sources/api/modeling/Env.rst.txt
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Env
===

.. doxygenclass:: idol::Env
6 changes: 6 additions & 0 deletions _sources/api/modeling/Expr.rst.txt
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.. _api_Expr:

Expr
====

.. doxygenclass:: idol::Expr
22 changes: 22 additions & 0 deletions _sources/api/modeling/LinExpr.rst.txt
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LinExpr
=======

This class is used to represent linear expressions in the modeling interface of idol.

It consists in a set of linear terms which represent products of keys (typically, variables) and scalars.

.. admonition:: Example

In this example, we create a linear expression representing the following linear expression.

.. math::
3 x_0 + 2 x_1
.. code-block:: cpp
auto x = model.add_vars(Dim<1>(2), 0, Inf, Continuous, "x");
LinExpr lin_expr = 3 * x[0] + 2 * x[1];
.. doxygenclass:: idol::LinExpr
55 changes: 55 additions & 0 deletions _sources/api/modeling/Model.rst.txt
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.. _api_model:

Model
=====

The Model class is probably the most central of idol. It is used to represent a mathematical optimization problem of the
following general form.

.. math::
\begin{array}{lll}
\textrm{minimize } & \displaystyle \sum_{j=1}^n a_{0j}x_j + \sum_{j=1}^n\sum_{k=1}^n q_{jk}^0x_jx_k + b_0\\
\textrm{subject to } & \displaystyle \sum_{j=1}^n a_{ij}x_j + \sum_{j=1}^n\sum_{k=1}^n q^i_{jk}x_jx_k \le b_i & i=1,...,m \\
& l_j \le x_j \le u_j & j=1,...,m \\
& x_j\in\mathbb Z & j\in J_I,
\end{array}
Here, :math:`x_1, ..., x_n` are the decision variables with bounds :math:`[l_1,u_1],...,[l_n,u_n]` (possibly,
:math:`l_j = -\infty` or :math:`u_j = +\infty`). Note that some variables have integrality requirements (i.e., those whose
indices are in :math:`J_I`). Other entities are input parameters of the problem and must typically have real values
(e.g., :math:`c_j, a_{ij}, q_{jk}^i` and :math:`b_i\in\mathbb R`). Alternatively, optimization problems can also be maximization
problems.

.. admonition:: Example:

Here is a short example which builds and solves the following optimization problem.

.. math::
\begin{array}{ll}
\textrm{minimize } & -x_0 - 1.5 x_1 + 3 \\
\textrm{subject to } & x_0 + 2 x_1 \le 1.5 \\
& 0 \le x_0 \le 1 \\
& 0 \le x_1 \le 1
\end{array}
.. code-block:: cpp
Env env;
Model model(env);
auto x = model.add_vars(Dim<1>(2), 0, 1, Continuous, "x");
auto c = model.add_ctr(x[0] + 2 * x[1] <= 1.5);
model.set_obj_expr(-x[0] - 1.5 * x[1] + 3);
model.use(Gurobi());
model.optimize();
std::cout << "Best obj = " << model.get_best_obj() << std::endl;
.. doxygenclass:: idol::Model
6 changes: 6 additions & 0 deletions _sources/api/modeling/Param.rst.txt
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.. _api_Param:

Param
=====

.. doxygenclass:: idol::Param
4 changes: 4 additions & 0 deletions _sources/api/modeling/QuadExpr.rst.txt
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QuadExpr
========

.. doxygenclass:: idol::QuadExpr
6 changes: 6 additions & 0 deletions _sources/api/modeling/Row.rst.txt
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.. _api_Row:

Row
===

.. doxygenclass:: idol::Row
6 changes: 6 additions & 0 deletions _sources/api/modeling/SolutionDual.rst.txt
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.. _api_SolutionDual:

Solution::Dual
================

.. doxygenclass:: idol::Solution::Dual
6 changes: 6 additions & 0 deletions _sources/api/modeling/SolutionPrimal.rst.txt
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.. _api_SolutionPrimal:

Solution::Primal
================

.. doxygenclass:: idol::Solution::Primal
6 changes: 6 additions & 0 deletions _sources/api/modeling/TempCtr.rst.txt
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.. _api_TempCtr:

TempCtr
=======

.. doxygenclass:: idol::TempCtr
6 changes: 6 additions & 0 deletions _sources/api/modeling/TempVar.rst.txt
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.. _api_TempVar:

TempVar
=======

.. doxygenclass:: idol::TempVar
6 changes: 6 additions & 0 deletions _sources/api/modeling/Var.rst.txt
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.. _api_var:

Var
===

.. doxygenclass:: idol::Var
10 changes: 10 additions & 0 deletions _sources/api/modeling/index.rst.txt
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.. _api_modeling:

Modeling
========

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

*
31 changes: 31 additions & 0 deletions _sources/api/optimizers/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 <api_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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.. _api_MostInfeasible:

MostInfeasible
==============

.. doxygenclass:: idol::MostInfeasible
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.. _api_branching_rules:

Branching rules
===============

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

MostInfeasible
13 changes: 13 additions & 0 deletions _sources/api/optimizers/branch-and-bound/index.rst.txt
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.. _api_branch_and_bound:

Branch-And-Bound algorithms
===========================

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

BranchAndBound
branching-rules/index
node-selection-rules/index
BranchAndBoundCallback
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.. _api_BestBound:

BestBound
=========

.. doxygenclass:: idol::BestBound
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.. _api_BreadthFirst:

BreadthFirst
============

.. doxygenclass:: idol::BreadthFirst
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.. _api_DepthFirst:

DepthFirst
==========

.. doxygenclass:: idol::DepthFirst
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