website: fix links
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</ol>
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</div><!-- class=shortcuts -->
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<ul class="badges">
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</ul>
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</nav> <!-- id=menu -->
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</div> <!-- id=alt -->
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@ -154,7 +151,7 @@
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<h2><a name="Gethelp"></a>Get help</h2>
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<p>If you need <em>immediate support or have any question</em>, the best way to get
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answers is to send an email to <a href='mailto:paradiseo-help@lists.gforge.inria.fr' rel='nofollow'>paradiseo-help@lists.gforge.inria.fr</a>. You can also <a href='http://lists.gforge.inria.fr/pipermail/paradiseo-help/' rel='nofollow'>consult the help archives</a>, subscribe to our <a href='http://lists.gforge.inria.fr/cgi-bin/mailman/listinfo/paradiseo-users' rel='nofollow'>(low traffic) mailing-list</a> or <a class='urllink' href='http://lists.gforge.inria.fr/pipermail/paradiseo-users/' rel='nofollow'>consult its archives</a>.
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answers is to send an email to <a href='mailto:paradiseo-help@lists.gforge.inria.fr'>paradiseo-help@lists.gforge.inria.fr</a>. You can also <a href='http://lists.gforge.inria.fr/pipermail/paradiseo-help/'>consult the help archives</a>, subscribe to our <a href='http://lists.gforge.inria.fr/cgi-bin/mailman/listinfo/paradiseo-users'>(low traffic) mailing-list</a> or <a href='http://lists.gforge.inria.fr/pipermail/paradiseo-users/'>consult its archives</a>.
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</p>
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<p>Alternatively, you can join us on the official chatroom. You can try our <a href="http://irc.lc/freenode/paradiseo">webchat interface</a>, or if you already use IRC, you can directly connect to the <a href="irc://irc.freenode.org/#paradiseo">irc.freenode.org/#paradiseo</a> multi-user chatroom with your favorite client.</p>
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@ -479,19 +476,19 @@ ISBN: 978-0-470-27858-1</blockquote>
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<div>
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<p><strong>Research Reports</strong>
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</p></div>
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<div></div><ul><li>J. Humeau, A. Liefooghe, E-G. Talbi, S. Verel <a class='urllink' href='http://hal.inria.fr/hal-00665421/' rel='nofollow'><em class="logo">Paradis<span class="logo_eo">eo</span></em>-MO: From Fitness Landscape Analysis to Efficient Local Search Algorithms</a>, Research Report RR-7871, INRIA, 2012.
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<div></div></li><li>A. Liefooghe, L. Jourdan, E.-G. Talbi, <a class='urllink' href='http://hal.inria.fr/inria-00376770/' rel='nofollow'>A Unified Model for Evolutionary Multiobjective Optimization and its Implementation in a General Purpose Software Framework: <em class="logo">Paradis<span class="logo_eo">eo</span></em>-MOEO</a>, Research Report RR-6906, INRIA, 2009.
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<div></div><ul><li>J. Humeau, A. Liefooghe, E-G. Talbi, S. Verel <a href='http://hal.inria.fr/hal-00665421/'><em class="logo">Paradis<span class="logo_eo">eo</span></em>-MO: From Fitness Landscape Analysis to Efficient Local Search Algorithms</a>, Research Report RR-7871, INRIA, 2012.
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<div></div></li><li>A. Liefooghe, L. Jourdan, E.-G. Talbi, <a href='http://hal.inria.fr/inria-00376770/'>A Unified Model for Evolutionary Multiobjective Optimization and its Implementation in a General Purpose Software Framework: <em class="logo">Paradis<span class="logo_eo">eo</span></em>-MOEO</a>, Research Report RR-6906, INRIA, 2009.
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</li></ul><div></div><div style='color: black; font-size: 10pt; background-color: #EEE;' >
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<p><strong>Journal papers</strong>
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</p></div>
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<div></div><ul><li>S. Cahon, N. Melab and E-G. Talbi, <a class='urllink' href='http://www.springerlink.com/content/up02m74726v1526u/' rel='nofollow'>"<em class="logo">Paradis<span class="logo_eo">eo</span></em>: A Framework for the Reusable Design of Parallel and Distributed Metaheuristics"</a>, Journal of Heuristics, vol. 10(3), pp.357-380, May 2004.
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<div></div></li><li> N. Melab, S. Cahon, E-G. Talbi.Grid computing for parallel bioinspired algorithms. <a class='urllink' href='http://top25.sciencedirect.com/index.php?cat_id=9&subject_area_id=7&journal_id=07437315' rel='nofollow'>Journal of Parallel and Distributed Computing (JPDC), Elsevier Science, Vol. 66(8), Pages 1052-1061, Aug. 2006.</a>
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<div></div></li><li>E-G. Talbi, S. Cahon and N. Melab. Designing cellular networks using a parallel hybrid metaheuristic. <a class='urllink' href='http://dx.doi.org/10.1016/j.comcom.2006.08.017' rel='nofollow'>Journal of Computer Communications, Elsevier Science, Vol. 30(4), Pages 698-713, 2007</a>
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<div></div><ul><li>S. Cahon, N. Melab and E-G. Talbi, <a href='https://link.springer.com/article/10.1023/B:HEUR.0000026900.92269.ec'>"<em class="logo">Paradis<span class="logo_eo">eo</span></em>: A Framework for the Reusable Design of Parallel and Distributed Metaheuristics"</a>, Journal of Heuristics, vol. 10(3), pp.357-380, May 2004.
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<div></div></li><li> N. Melab, S. Cahon, E-G. Talbi, Grid computing for parallel bioinspired algorithms. <a href='https://www.sciencedirect.com/science/article/abs/pii/S0743731506000189'>Journal of Parallel and Distributed Computing (JPDC), Elsevier Science, Vol. 66(8), Pages 1052-1061, Aug. 2006.</a>
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<div></div></li><li>E-G. Talbi, S. Cahon and N. Melab. Designing cellular networks using a parallel hybrid metaheuristic. <a href='http://dx.doi.org/10.1016/j.comcom.2006.08.017'>Journal of Computer Communications, Elsevier Science, Vol. 30(4), Pages 698-713, 2007</a>
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<div></div></li><li>S. Cahon, N. Melab and E-G. Talbi, "Building with <em class="logo">Paradis<span class="logo_eo">eo</span></em> reusible parallel and distributed evolutionary algorithms", Parallel Computing, vol.30(5-6), pp.677-697, June 2004.
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</li></ul><div></div><div style='color: black; font-size: 10pt; background-color: #EEE;' >
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<p><strong>Conference papers</strong>
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</p></div>
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<div></div><ul><li>A. Liefooghe, M. Basseur, L. Jourdan, E.-G. Talbi, <a class='urllink' href='http://www2.lifl.fr/~jourdan/publi/jourdan_EMO07_A.pdf' rel='nofollow'>"<em class="logo">Paradis<span class="logo_eo">eo</span></em>-MOEO: A Framework for Evolutionary Multi-objective Optimization"</a>, EMO 2007, LNCS Vol. 4403, pp. 386-400, Matsushima, Japan.
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<div></div><ul><li>A. Liefooghe, M. Basseur, L. Jourdan, E.-G. Talbi, <a href='https://link.springer.com/chapter/10.1007/978-3-540-70928-2_31'>"<em class="logo">Paradis<span class="logo_eo">eo</span></em>-MOEO: A Framework for Evolutionary Multi-objective Optimization"</a>, EMO 2007, LNCS Vol. 4403, pp. 386-400, Matsushima, Japan.
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<div></div></li><li>S. Cahon, N. Melab and E-G. Talbi, "<em class="logo">Paradis<span class="logo_eo">eo</span></em>: a framework for metaheuristics", International Workshop on Optimization Frameworks for Industrial Applications (ICOPI 2005), Paris, France, October 19-21, 2005.
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<div></div></li><li>S. Cahon, N. Melab and E-G. Talbi, "An Enabling Framework for Parallel Optimization on the Computational Grid", In Proceedings of the fifth IEEE/ACM International Symposium on Cluster Computing and the Grid (CCGRID'2005), Cardiff, UK, May, 2005.
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<div></div></li><li> S. Cahon, N. Melab, E-G. Talbi and M. Schoenauer, "PARADISEO based design of parallel and distributed evolutionary algorithms", Evolutionary Algorithms EA'2003, Marseille, France, LNCS, October 2003.
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@ -525,7 +522,7 @@ ISBN: 978-0-470-27858-1</blockquote>
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<p>The flow-shop is one of the most widely investigated scheduling problem of the literature. But, the majority of studies considers it on a single-criterion form. However, other objectives than minimizing the makespan can be taken into account, like, e.g., minimizing the total tardiness.
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</p>
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<p>Ref:
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</p><ul><li>Arnaud Liefooghe, Matthieu Basseur, Laetitia Jourdan, El-Ghazali Talbi. "Combinatorial Optimization of Stochastic Multi-objective Problems: an Application to the Flow-shop Scheduling Problem". In S. Obayashi et al. (Eds.): Evolutionary Multi-Criterion Optimization (<a class='urllink' href='http://www.is.doshisha.ac.jp/emo2007/' rel='nofollow'>EMO 2007</a>), LNCS vol. 4403, pp. 457-471, Matsushima, Japan (2007)
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</p><ul><li>Arnaud Liefooghe, Matthieu Basseur, Laetitia Jourdan, El-Ghazali Talbi. "Combinatorial Optimization of Stochastic Multi-objective Problems: an Application to the Flow-shop Scheduling Problem". In S. Obayashi et al. (Eds.): Evolutionary Multi-Criterion Optimization (<a href='http://www.is.doshisha.ac.jp/emo2007/'>EMO 2007</a>), LNCS vol. 4403, pp. 457-471, Matsushima, Japan (2007)
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</li></ul>
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<h3>Electromagnetic properties of conducting polymer composites in the microwave band.</h3>
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@ -570,13 +567,13 @@ undiscovered knowledge.
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<li>J.J. Gilijamse, J. Küpper, S. Hoekstra, S.Y.T. van de Meerakker, G. Meijer,
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<a href= "http://dx.doi.org/10.1103/PhysRevA.73.063410">Optimizing the Stark-decelerator beamline for the trapping of cold molecules using evolutionary strategies</a>,
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<i> Physical Review</i>, A <b>73</b>, 063410 (2006). <br/>
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Also available at <a href= "http://arxiv.org/abs/physics/0603108"><i>arXiv</i>
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Also available at <a href="https://arxiv.org/abs/physics/0603108"><i>arXiv</i>
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physics/0603108 (2006)</a>.</li>
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</ul>
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<h3>Metaheuristics Design</h3>
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<ul>
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<li>Johann Dreo, <a href="http://www.nojhan.net/pro/spip.php?article31">Using Performance Fronts for Parameter Setting of Stochastic Metaheuristics</a>, <i>Genetic and Evolutionary Computation Conference</i>, (2009).</li>
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<li>Johann Dreo, <a href="https://dl.acm.org/doi/10.1145/1570256.1570301">Using Performance Fronts for Parameter Setting of Stochastic Metaheuristics</a>, <i>Genetic and Evolutionary Computation Conference</i>, (2009).</li>
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</ul>
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</div>
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@ -590,37 +587,37 @@ undiscovered knowledge.
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<ul>
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<li> A functional and "philosophical" overview of the EO module was presented at <a href="http://www.cmap.polytechnique.fr/%7Eea01/">EA'01 conference</a>.
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You can download <a href="http://eodev.sourceforge.net/eo/doc/EO_EA2001.pdf">the paper</a>
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or <a href="http://eodev.sourceforge.net/eo/doc/LeCreusot.pdf">the
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You can download <a href="https://www.lri.fr/~marc/EO/eo/doc/EO_EA2001.pdf">the paper</a>
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or <a href="https://www.lri.fr/~marc/EO/eo/doc/LeCreusot.pdf">the
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slides</a>.</li>
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<li><strong><a class='urllink' href='http://paradiseo.gforge.inria.fr/addon/paradiseo-eo/concepts/paradiseo-eo-design.pdf' rel='nofollow'>Metaheuristics for Combinatorial Optimization</a></strong> [pdf] by E-G. Talbi and S.Cahon: provides general concept on metaheuristics for combinatorial optimization.
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</li><li><strong><a class='urllink' href='http://paradiseo.gforge.inria.fr/addon/paradiseo-eo/concepts/paradiseo-eo-implem.pdf' rel='nofollow'>Reusable Design of Metaheuristics</a></strong> [pdf] by S.Cahon, E-G. Talbi and N. Melab: explains how to use Paradiseo-EO with a simple example.
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<li><strong><a href='http://paradiseo.gforge.inria.fr/addon/paradiseo-eo/concepts/paradiseo-eo-design.pdf'>Metaheuristics for Combinatorial Optimization</a></strong> [pdf] by E-G. Talbi and S.Cahon: provides general concept on metaheuristics for combinatorial optimization.
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</li><li><strong><a href='http://paradiseo.gforge.inria.fr/addon/paradiseo-eo/concepts/paradiseo-eo-implem.pdf'>Reusable Design of Metaheuristics</a></strong> [pdf] by S.Cahon, E-G. Talbi and N. Melab: explains how to use Paradiseo-EO with a simple example.
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</li></ul>
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<h3>Paradiseo-MO</h3>
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<ul><li><strong><a class='urllink' href='http://paradiseo.gforge.inria.fr/addon/paradiseo-mo/concepts/paradiseo-newmo-design.pdf' rel='nofollow'>Reusable Design of Local Searches and Tools for Landscape Analysis</a></strong> [pdf] by S.Verel, A.Liefooghe and J.Humeau: explains the new design of Paradiseo-MO.
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</li><li><strong><a class='urllink' href='https://dl.dropboxusercontent.com/u/3098761/dolphin/paradiseo_roadef2012.pdf' rel='nofollow'><em class="logo">Paradis<span class="logo_eo">eo</span></em>-MO: From fitness landscape analysis to efficient local search algorithms</a></strong> [pdf] by J.Humeau, A.Liefooghe, E-G. Talbi, and S.Verel (presented at ROADEF 2012).
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<ul><li><strong><a href='http://paradiseo.gforge.inria.fr/addon/paradiseo-mo/concepts/paradiseo-newmo-design.pdf'>Reusable Design of Local Searches and Tools for Landscape Analysis</a></strong> [pdf] by S.Verel, A.Liefooghe and J.Humeau: explains the new design of Paradiseo-MO.
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</li><li><strong><a href='https://hal.inria.fr/hal-00665421v2'><em class="logo">Paradis<span class="logo_eo">eo</span></em>-MO: From fitness landscape analysis to efficient local search algorithms</a></strong> [pdf] by J.Humeau, A.Liefooghe, E-G. Talbi, and S.Verel (presented at ROADEF 2012).
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</li></ul>
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<h3>Paradiseo-MOEO</h3>
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<ul><li><strong><a class='urllink' href='http://paradiseo.gforge.inria.fr/addon/paradiseo-moeo/concepts/paradiseo-moeo-design.pdf' rel='nofollow'>Metaheuristics for Multi-objective Optimization</a></strong> [pdf] by E.-G. Talbi and the <em class="logo">Paradis<span class="logo_eo">eo</span></em> group: presents multi-objective optimization concepts, a taxonomy of resolution methods and gives performance evaluation examples.
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</li><li><strong><a class='urllink' href='http://paradiseo.gforge.inria.fr/addon/paradiseo-moeo/concepts/paradiseo-moeo-implem.pdf' rel='nofollow'>Reusable Design of Metaheuristics for Multi-objective Optimization</a></strong> [pdf] by E.-G. Talbi and the <em class="logo">Paradis<span class="logo_eo">eo</span></em> group: explains how to implement metaheuristics for multi-objective optimization using Paradiseo-MOEO through a simple example.
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<ul><li><strong><a href='http://paradiseo.gforge.inria.fr/addon/paradiseo-moeo/concepts/paradiseo-moeo-design.pdf'>Metaheuristics for Multi-objective Optimization</a></strong> [pdf] by E.-G. Talbi and the <em class="logo">Paradis<span class="logo_eo">eo</span></em> group: presents multi-objective optimization concepts, a taxonomy of resolution methods and gives performance evaluation examples.
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</li><li><strong><a href='http://paradiseo.gforge.inria.fr/addon/paradiseo-moeo/concepts/paradiseo-moeo-implem.pdf'>Reusable Design of Metaheuristics for Multi-objective Optimization</a></strong> [pdf] by E.-G. Talbi and the <em class="logo">Paradis<span class="logo_eo">eo</span></em> group: explains how to implement metaheuristics for multi-objective optimization using Paradiseo-MOEO through a simple example.
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</li></ul>
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<!-- <h3>Paradiseo-PEO</h3> -->
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<!-- -->
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<!-- <ul> -->
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<!-- <li>If you want to understand the message-passing parallelization module, check the <a href="http://eodev.sourceforge.net/eo/tutorial/Parallelization/eompi.html">introduction to eo::MPI</a> by Benjamin Bouvier.</li> -->
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<!-- <li><strong><a class='urllink' href='http://paradiseo.gforge.inria.fr/addon/paradiseo-peo/concepts/paradiseo-peo-design.pdf' rel='nofollow'>Parallel and Hybrid Metaheuristics</a></strong> [pdf] by E-G. Talbi, S.Cahon and N. Melab: defines metaheuristics parallelization and hybridation and presents implementation models threatened with Paradiseo-PEO to solve a industrial problem. -->
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<!-- </li><li><strong> <a class='urllink' href='http://paradiseo.gforge.inria.fr/addon/paradiseo-peo/concepts/paradiseo-peo-implem.pdf' rel='nofollow'>Reusable Design of Parallel and Distributed Evolving Object</a></strong> [pdf] by N. Melab, E.-G. Talbi, S. Cahon and A. Tantar: explains how to implement metaheuristics for parallel and distributed optimization using Paradiseo-PEO through a few simple examples. -->
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<!-- <li><strong><a href='http://paradiseo.gforge.inria.fr/addon/paradiseo-peo/concepts/paradiseo-peo-design.pdf'>Parallel and Hybrid Metaheuristics</a></strong> [pdf] by E-G. Talbi, S.Cahon and N. Melab: defines metaheuristics parallelization and hybridation and presents implementation models threatened with Paradiseo-PEO to solve a industrial problem. -->
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<!-- </li><li><strong> <a href='http://paradiseo.gforge.inria.fr/addon/paradiseo-peo/concepts/paradiseo-peo-implem.pdf'>Reusable Design of Parallel and Distributed Evolving Object</a></strong> [pdf] by N. Melab, E.-G. Talbi, S. Cahon and A. Tantar: explains how to implement metaheuristics for parallel and distributed optimization using Paradiseo-PEO through a few simple examples. -->
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<!-- </li></ul> -->
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<!-- <h3>Paradiseo-OLD-MO</h3> -->
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<!-- -->
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<!-- <ul><li><strong><a class='urllink' href='http://paradiseo.gforge.inria.fr/addon/paradiseo-oldmo/concepts/paradiseo-mo-design.pdf' rel='nofollow'>Single Solution-based Metaheuristics</a></strong> [pdf] by E-G. Talbi and S.Cahon: describes the general concept of solution-based metaheuristics and provides examples applied to TSP problem -->
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<!-- </li><li><strong><a class='urllink' href='http://paradiseo.gforge.inria.fr/addon/paradiseo-oldmo/concepts/paradiseo-mo-implem.pdf' rel='nofollow'>Reusable Design of Solution-based Metaheuristics</a></strong> [pdf] by S.Cahon, E-G. Talbi and N. Melab: explains how to implement metaheuristics thanks to Paradiseo-MO through a TSP example -->
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<!-- <ul><li><strong><a href='http://paradiseo.gforge.inria.fr/addon/paradiseo-oldmo/concepts/paradiseo-mo-design.pdf'>Single Solution-based Metaheuristics</a></strong> [pdf] by E-G. Talbi and S.Cahon: describes the general concept of solution-based metaheuristics and provides examples applied to TSP problem -->
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<!-- </li><li><strong><a href='http://paradiseo.gforge.inria.fr/addon/paradiseo-oldmo/concepts/paradiseo-mo-implem.pdf'>Reusable Design of Solution-based Metaheuristics</a></strong> [pdf] by S.Cahon, E-G. Talbi and N. Melab: explains how to implement metaheuristics thanks to Paradiseo-MO through a TSP example -->
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<!-- </li></ul> -->
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<h2><a name="Tutorials"></a>Tutorials</h2>
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@ -629,53 +626,53 @@ undiscovered knowledge.
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<h3>Tutorials on EO (evolutionary algorithms module)</h3>
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<ul><li><a class='urllink' href='http://eodev.sourceforge.net/eo/tutorial/html/eoTutorial.html' rel='nofollow'>EO Lesson1-5</a> <strong>Implement a GA</strong>
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</li><li><a class='wikilink' href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoEOLesson6part1'>EO Lesson6 first part</a> <strong>Implement a real PSO algorithm</strong>
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</li><li><a class='wikilink' href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoEOLesson6part2'>EO Lesson6 second part</a> <strong>Implement a binary PSO algorithm</strong>
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<ul><li><a href='http://eodev.sourceforge.net/eo/tutorial/html/eoTutorial.html'>EO Lesson1-5</a> <strong>Implement a GA</strong>
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</li><li><a href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoEOLesson6part1'>EO Lesson6 first part</a> <strong>Implement a real PSO algorithm</strong>
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</li><li><a href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoEOLesson6part2'>EO Lesson6 second part</a> <strong>Implement a binary PSO algorithm</strong>
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</li></ul>
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<h3>Tutorials MO (local search module)</h3>
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</p><ul><li><a class='wikilink' href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoMOLesson1'>MO Lesson1</a> <strong>Hill Climber</strong>
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</li><li><a class='wikilink' href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoMOLesson2'>MO Lesson2</a> <strong>Neighborhoods</strong> (classical and indexed)
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</li><li><a class='wikilink' href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoMOLesson3'>MO Lesson3</a> <strong>Simulated Annealing</strong> and <strong>Checkpointing</strong>
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</li><li><a class='wikilink' href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoMOLesson4'>MO Lesson4</a> <strong>Tabu Search</strong>
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</li><li><a class='wikilink' href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoMOLesson5'>MO Lesson5</a> <strong>Iterated Local Search</strong>
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</li><li><a class='wikilink' href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoMOLesson6'>MO Lesson6</a> <strong>Fitness Landscapes Analysis</strong>
|
||||
</li><li><a class='wikilink' href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoMOLesson7'>MO Lesson7</a> <strong>Hybrid Lesson</strong>
|
||||
</p><ul><li><a href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoMOLesson1'>MO Lesson1</a> <strong>Hill Climber</strong>
|
||||
</li><li><a href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoMOLesson2'>MO Lesson2</a> <strong>Neighborhoods</strong> (classical and indexed)
|
||||
</li><li><a href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoMOLesson3'>MO Lesson3</a> <strong>Simulated Annealing</strong> and <strong>Checkpointing</strong>
|
||||
</li><li><a href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoMOLesson4'>MO Lesson4</a> <strong>Tabu Search</strong>
|
||||
</li><li><a href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoMOLesson5'>MO Lesson5</a> <strong>Iterated Local Search</strong>
|
||||
</li><li><a href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoMOLesson6'>MO Lesson6</a> <strong>Fitness Landscapes Analysis</strong>
|
||||
</li><li><a href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoMOLesson7'>MO Lesson7</a> <strong>Hybrid Lesson</strong>
|
||||
</li></ul>
|
||||
|
||||
<h3>Tutorials MOEO (multi-objective module)</h3>
|
||||
|
||||
</p><ul><li><a class='wikilink' href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoMOEOLesson1'>MOEO Lesson1</a> <strong>Implement NSGA, NSGA-II and IBEA for the SCH1 problem</strong>
|
||||
</li><li><a class='wikilink' href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoMOEOLesson2'>MOEO Lesson2</a> <strong>Evolutionary Algorithms for the flow-shop scheduling problem</strong>
|
||||
</li><li><a class='wikilink' href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoMOEOLesson3'>MOEO Lesson3</a> <strong>Evolutionary Algorithms with a user-friendly parameter file</strong>
|
||||
</li><li><a class='wikilink' href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoMOEOLesson4'>MOEO Lesson4</a> <strong>Dominance-based Local Search for the flow-shop scheduling problem</strong>
|
||||
</p><ul><li><a href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoMOEOLesson1'>MOEO Lesson1</a> <strong>Implement NSGA, NSGA-II and IBEA for the SCH1 problem</strong>
|
||||
</li><li><a href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoMOEOLesson2'>MOEO Lesson2</a> <strong>Evolutionary Algorithms for the flow-shop scheduling problem</strong>
|
||||
</li><li><a href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoMOEOLesson3'>MOEO Lesson3</a> <strong>Evolutionary Algorithms with a user-friendly parameter file</strong>
|
||||
</li><li><a href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoMOEOLesson4'>MOEO Lesson4</a> <strong>Dominance-based Local Search for the flow-shop scheduling problem</strong>
|
||||
</li></ul><p><strong>Tutorials SMP:</strong> <span style='color: red;'> <strong> new</strong></span>
|
||||
</p><ul><li><a class='wikilink' href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoSMPLesson1'>SMP Lesson1</a> <strong>Algorithm wrapping with Master / Workers model</strong>
|
||||
</p><ul><li><a href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoSMPLesson1'>SMP Lesson1</a> <strong>Algorithm wrapping with Master / Workers model</strong>
|
||||
</li></ul>
|
||||
|
||||
<!-- <h3>Tutorials PEO (one of the parallelization modules)</h3> -->
|
||||
<!-- </p><ul><li><a class='wikilink' href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoPEOIntro'>PEO Intro</a> <strong>Technical introduction</strong> -->
|
||||
<!-- </li><li><a class='wikilink' href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoPEOLesson1'>PEO Lesson1</a> <strong>Multistart over a MO, Packing and Unpacking </strong> (use old-mo) -->
|
||||
<!-- </li><li><a class='wikilink' href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoPEOLesson2'>PEO Lesson2</a> <strong>Multistart over an evolutionary algorithm</strong> -->
|
||||
<!-- </li><li><a class='wikilink' href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoPEOLesson3'>PEO Lesson3</a> <strong>Parallel evaluation </strong> -->
|
||||
<!-- </li><li><a class='wikilink' href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoPEOLesson4'>PEO Lesson4</a> <strong>Parallel transformation</strong> (use old-mo) -->
|
||||
<!-- </li><li><a class='wikilink' href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoPEOLesson5'>PEO Lesson5</a> <strong>Island model</strong> -->
|
||||
<!-- </li><li><a class='wikilink' href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoPEOLesson6'>PEO Lesson6</a> <strong>Hybridization</strong> (use old-mo) -->
|
||||
<!-- </p><ul><li><a href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoPEOIntro'>PEO Intro</a> <strong>Technical introduction</strong> -->
|
||||
<!-- </li><li><a href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoPEOLesson1'>PEO Lesson1</a> <strong>Multistart over a MO, Packing and Unpacking </strong> (use old-mo) -->
|
||||
<!-- </li><li><a href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoPEOLesson2'>PEO Lesson2</a> <strong>Multistart over an evolutionary algorithm</strong> -->
|
||||
<!-- </li><li><a href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoPEOLesson3'>PEO Lesson3</a> <strong>Parallel evaluation </strong> -->
|
||||
<!-- </li><li><a href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoPEOLesson4'>PEO Lesson4</a> <strong>Parallel transformation</strong> (use old-mo) -->
|
||||
<!-- </li><li><a href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoPEOLesson5'>PEO Lesson5</a> <strong>Island model</strong> -->
|
||||
<!-- </li><li><a href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoPEOLesson6'>PEO Lesson6</a> <strong>Hybridization</strong> (use old-mo) -->
|
||||
<!-- </li></ul><p><span style='display: none;'><strong>GPU tutorials:</strong> </span> -->
|
||||
<!-- <span style='display: none;'>*<a class='wikilink' href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoGPULesson1'>GPU Lesson1</a> <strong>CUDA installation and configuration</strong></span> -->
|
||||
<!-- <span style='display: none;'>*<a class='wikilink' href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoGPULesson2'>GPU Lesson2</a> <strong>Prerequisites: How to configure Paradiseo-GPU</strong></span> -->
|
||||
<!-- <span style='display: none;'>*<a class='wikilink' href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoGPULesson3'>GPU Lesson3</a> <strong>Prerequisites: How to define solution on GPU</strong></span> -->
|
||||
<!-- <span style='display: none;'>*<a class='wikilink' href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoGPULesson4'>GPU Lesson4</a> <strong>Prerequisites: How to define neighbor & neighborhood on GPU</strong></span> -->
|
||||
<!-- <span style='display: none;'>*<a class='wikilink' href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoGPULesson5'>GPU Lesson5</a> <strong>Prerequisites: How to evaluate solution & neighbor on GPU</strong></span> -->
|
||||
<!-- <span style='display: none;'>*<a class='wikilink' href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoGPULesson6'>GPU Lesson6</a> <strong>Hill Climbing and Tabu Search on GPU</strong></span> -->
|
||||
<!-- <span style='display: none;'>*<a href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoGPULesson1'>GPU Lesson1</a> <strong>CUDA installation and configuration</strong></span> -->
|
||||
<!-- <span style='display: none;'>*<a href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoGPULesson2'>GPU Lesson2</a> <strong>Prerequisites: How to configure Paradiseo-GPU</strong></span> -->
|
||||
<!-- <span style='display: none;'>*<a href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoGPULesson3'>GPU Lesson3</a> <strong>Prerequisites: How to define solution on GPU</strong></span> -->
|
||||
<!-- <span style='display: none;'>*<a href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoGPULesson4'>GPU Lesson4</a> <strong>Prerequisites: How to define neighbor & neighborhood on GPU</strong></span> -->
|
||||
<!-- <span style='display: none;'>*<a href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoGPULesson5'>GPU Lesson5</a> <strong>Prerequisites: How to evaluate solution & neighbor on GPU</strong></span> -->
|
||||
<!-- <span style='display: none;'>*<a href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoGPULesson6'>GPU Lesson6</a> <strong>Hill Climbing and Tabu Search on GPU</strong></span> -->
|
||||
<!-- </p> -->
|
||||
|
||||
<h3>Utilities</h3>
|
||||
|
||||
</p><ul><li><a class='wikilink' href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoUtilsParamFiles'>Utils Lesson1</a> <strong>Using configuration files</strong>
|
||||
</li><li><a class='wikilink' href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoUtilsStats'>Utils Lesson2</a> <strong>Using statistics</strong>
|
||||
</p><ul><li><a href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoUtilsParamFiles'>Utils Lesson1</a> <strong>Using configuration files</strong>
|
||||
</li><li><a href='http://paradiseo.gforge.inria.fr/index.php?n=Doc.TutoUtilsStats'>Utils Lesson2</a> <strong>Using statistics</strong>
|
||||
</li></ul>
|
||||
|
||||
<h2><a name="API"></a>API documentation</h2>
|
||||
|
|
@ -684,11 +681,11 @@ undiscovered knowledge.
|
|||
|
||||
<p>For your convenience, you can browse an online API doc for <em class="logo">Paradis<span class="logo_eo">eo</span></em> version 2.0:
|
||||
<ul>
|
||||
<li><a href='http://paradiseo.gforge.inria.fr/addon/eo/doc/index.html' rel='nofollow'>doc-eo</a> </li>
|
||||
<li><a href='http://paradiseo.gforge.inria.fr/addon/eo/doc/index.html'>doc-eo</a> </li>
|
||||
<li>doc-edo (missing link)</li>
|
||||
<li><a href='http://paradiseo.gforge.inria.fr/addon/mo/doc/index.html' rel='nofollow'>doc-mo</a> </li>
|
||||
<li><a href='http://paradiseo.gforge.inria.fr/addon/moeo/doc/index.html' rel='nofollow'>doc-moeo</a> </li>
|
||||
<li><a href='http://paradiseo.gforge.inria.fr/addon/smp/doc/index.html' rel='nofollow'>doc-smp</a> </li>
|
||||
<li><a href='http://paradiseo.gforge.inria.fr/addon/mo/doc/index.html'>doc-mo</a> </li>
|
||||
<li><a href='http://paradiseo.gforge.inria.fr/addon/moeo/doc/index.html'>doc-moeo</a> </li>
|
||||
<li><a href='http://paradiseo.gforge.inria.fr/addon/smp/doc/index.html'>doc-smp</a> </li>
|
||||
</ul>
|
||||
</p>
|
||||
|
||||
|
|
@ -790,7 +787,7 @@ undiscovered knowledge.
|
|||
|
||||
<p><em class="logo">Paradis<span class="logo_eo">eo</span></em> development is open and contributions are welcomed.</p>
|
||||
<p>The official bug tracker is available on the <a href="https://gforge.inria.fr/projects/paradiseo/">project page</a>. But you may be more confortable using the <a href="https://github.com/nojhan/paradiseo/issues">issue tracker of Johann Dreo's project page on GitHub</a>.</p>
|
||||
<p>If you have any question about contributing: subscribe to our <a href='http://lists.gforge.inria.fr/cgi-bin/mailman/listinfo/paradiseo-users' rel='nofollow'>(low traffic) mailing-list</a>.</p>
|
||||
<p>If you have any question about contributing: subscribe to our <a href='http://lists.gforge.inria.fr/cgi-bin/mailman/listinfo/paradiseo-users'>(low traffic) mailing-list</a>.</p>
|
||||
|
||||
<!-- HISTORY -->
|
||||
<h1><a name="History"></a>History <a href="#Plan">⤒</a></h1>
|
||||
|
|
@ -843,18 +840,23 @@ undiscovered knowledge.
|
|||
and <a href="http://www.jochen-kuepper.de">Jochen Küpper</a>, working on
|
||||
infrastructure maintenance. </p>
|
||||
|
||||
<p>El-Ghazali Talbi's INRIA team did a lot of contributions starting from around 2003,
|
||||
<p><a href="https://www.lifl.fr/~talbi/">El-Ghazali Talbi</a>'s
|
||||
INRIA team did a lot of contributions starting from around 2003,
|
||||
on their own module collection called <em class="logo">Paradis<span class="logo_eo">eo</span></em>.
|
||||
Thomas Legrand, S. Cahon and N.Melab worked on parallelization modules.
|
||||
Arnaud Liefooghe worked a lot on the multi-objective module and
|
||||
on the local-search one along with Sébastien Verel and Jeremy Humeau.
|
||||
Thomas Legrand, Sébastien Cahon and <a href="https://www.lifl.fr/~melab">Nouredine Melab</a>
|
||||
worked on parallelization modules.
|
||||
<a href="https://sites.google.com/site/arnaudliefooghe/">Arnaud Liefooghe</a>
|
||||
worked a lot on the multi-objective module and
|
||||
on the local-search one along with <a href="https://www-lisic.univ-littoral.fr/~verel/">Sébastien Verel</a>
|
||||
and Jeremy Humeau.
|
||||
In the same team, Clive Canape and J. Boisson made significant contributions.
|
||||
Karima Boufaras specifically worked on (now deprecated) GPU tools.</p>
|
||||
|
||||
<p>The (then) EO project was then taken over by <a href="http://johann.dreo.fr">Johann Dreo</a>,
|
||||
who worked with the help of <a href="http://caner.candan.fr">Caner Candan</a> on adding the EDO module.
|
||||
Johann and <a href="https://github.com/BenjBouv">Benjamin Bouvier</a> have also designed a
|
||||
MPI parallelization module. Alexandre Quemy also worked on parallelization codes.</p>
|
||||
who worked with the help of Caner Candan on adding the EDO module.
|
||||
Johann and <a href="https://github.com/bnjbvr">Benjamin Bouvier</a> have also designed a
|
||||
MPI parallelization module. <a href="https://aquemy.info/">Alexandre Quemy</a>
|
||||
also worked on parallelization codes.</p>
|
||||
|
||||
<p>In 2012, the two project (EO and <em class="logo">Paradis<span class="logo_eo">eo</span></em>) were merged in a single one
|
||||
by Johann Dreo, Sébastien Verel and Arnaud Liefooghe, who act as maintainers ever since.</p>
|
||||
|
|
|
|||
|
|
@ -41,16 +41,6 @@ pre {
|
|||
margin:0.2em;
|
||||
}
|
||||
|
||||
ul.badges {
|
||||
list-style-type:none;
|
||||
margin-top:2em;
|
||||
}
|
||||
|
||||
ul.badges li {
|
||||
margin-left:0px;
|
||||
margin-top:0.5em;
|
||||
}
|
||||
|
||||
#alt {
|
||||
font-size:small;
|
||||
float:left;
|
||||
|
|
@ -68,8 +58,6 @@ ul.badges li {
|
|||
}
|
||||
|
||||
#toc {
|
||||
/* background-color:#222; */
|
||||
/* padding: 0.01em 0.5em 0.1em 0.5em; */
|
||||
}
|
||||
|
||||
|
||||
|
|
@ -84,9 +72,6 @@ ul.badges li {
|
|||
font-weight:normal;
|
||||
font-style:italic;
|
||||
padding:1em;
|
||||
/* padding:18px 0px 0px 50px; */
|
||||
/* float:left; */
|
||||
/* margin:0px 0px 10px 0px; */
|
||||
}
|
||||
|
||||
nav {
|
||||
|
|
@ -202,34 +187,6 @@ a:hover {
|
|||
text-decoration:underline;
|
||||
}
|
||||
|
||||
#appendix {
|
||||
background:url("Purine_Nucleoside_Phosphorylase_small.jpg");
|
||||
background-repeat:no-repeat;
|
||||
background-position:top right;
|
||||
}
|
||||
|
||||
#title {
|
||||
color:#3366CC;
|
||||
/*background-color:#FFFFFF;*/
|
||||
font-size:3em;
|
||||
font-weight:bold;
|
||||
margin:0px 0px 10px 0px;
|
||||
float:left;
|
||||
}
|
||||
|
||||
ul#login {
|
||||
margin:0px;
|
||||
padding:0px;
|
||||
list-style: none;
|
||||
position:absolute;
|
||||
top:0px;
|
||||
right:1em;
|
||||
}
|
||||
|
||||
ul#login li {
|
||||
display:inline;
|
||||
}
|
||||
|
||||
ul#menu {
|
||||
clear:both;
|
||||
margin: 0;
|
||||
|
|
@ -261,72 +218,6 @@ ul#menu li a:hover { background: #3366CC; color: #FFFFFF; }
|
|||
ul#menu a.selected:link { background: #3366CC; color: #FFFFFF; }
|
||||
ul#menu a.selected:visited { background: #3366CC; color: #FFFFFF; }
|
||||
|
||||
#page {
|
||||
font-size:1.0em;
|
||||
padding:1em;
|
||||
margin:1em;
|
||||
/*width:650px;
|
||||
float:left;*/
|
||||
clear:left;
|
||||
}
|
||||
|
||||
|
||||
#foot {
|
||||
color:#000000;
|
||||
background-color:#FFFFFF;
|
||||
border-top:1px solid #0033CC;
|
||||
font-size:80%;
|
||||
/*line-height:1.5em;*/
|
||||
/*width: 650px;*/
|
||||
clear:both;
|
||||
}
|
||||
|
||||
#foot a {
|
||||
color:#3366CC;
|
||||
background-color:#FFFFFF;
|
||||
text-decoration: none;
|
||||
}
|
||||
|
||||
#foot a:hover {
|
||||
color:#0033CC;
|
||||
background-color:#FFFFFF;
|
||||
font-weight: normal;
|
||||
text-decoration: underline;
|
||||
}
|
||||
|
||||
#copyright {
|
||||
color:#000000;
|
||||
background-color:#FFFFFF;
|
||||
padding:5px 20px 5px 0px;
|
||||
float:left;
|
||||
}
|
||||
|
||||
#contact {
|
||||
color:#0033CC;
|
||||
background-color:#FFFFFF;
|
||||
padding:5px 0px 5px 0px;
|
||||
float:right;
|
||||
}
|
||||
|
||||
|
||||
.table_form_title {
|
||||
font-weight:bold;
|
||||
}
|
||||
|
||||
.table_form_label {
|
||||
text-align:right;
|
||||
padding-right:1em;
|
||||
}
|
||||
|
||||
.table_form_submit {
|
||||
text-align:center;
|
||||
}
|
||||
|
||||
.legend {
|
||||
font-style:italic;
|
||||
font-size:80%;
|
||||
}
|
||||
|
||||
.collapsible {
|
||||
background-color: #eee;
|
||||
color:#36C;
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue