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@section Introduction
ParadisEO-MO is a white-box object-oriented generic framework dedicated to the flexible design of local search algorithms.
ParadisEO-MO is a white-box object-oriented generic framework dedicated to the flexible design of local search algorithms (hill-climbing, tabu search, simulated annealing, ...)
@section tutorials Tutorials
Tutorials for ParadisEO-MO are available in the "Tutorials section" of the <a href="http://paradiseo.gforge.inria.fr">ParadisEO website</a>.
@section Design
For an introduction to the design of ParadisEO-MO,
you can look at the <a href="http://paradiseo.gforge.inria.fr">ParadisEO website</a>.
@section LICENSE

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It is based on a clear conceptual distinction between the solution methods and the multi-objective problems they are intended to solve.
This separation confers a maximum design and code reuse.
ParadisEO-MOEO provides a broad range of archive-related features (such as elitism or performance metrics)
and the most common Pareto-based fitness assignment strategies (MOGA, NSGA, SPEA, IBEA and more).
and the most common Pareto-based fitness assignment strategies (MOGA, NSGA, SPEA, IBEA and more). Dominance-based Local Search are also available.
Furthermore, parallel and distributed models as well as hybridization mechanisms can be applied to an algorithm designed within ParadisEO-MOEO
using the whole version of ParadisEO.
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@section tutorials Tutorials
Tutorials for ParadisEO-MOEO are available <a href="http://paradiseo.gforge.inria.fr/index.php?n=Paradiseo.UsersGuides">here</a>.
Tutorials for ParadisEO-MOEO are available in the "Tutorials section" of the <a href="http://paradiseo.gforge.inria.fr">ParadisEO website</a>.
@section Installation
The installation procedure of the package is detailed in the <a
href="../../README">README</a> file in the top-directory of the source-tree.
The installation procedure of the package is detailed in the README file in the top-directory of the source-tree.