ParadisEO-MO: From Fitness Landscape Analysis to Efficient Local Search Algorithms

Abstract : This paper presents a general-purpose software framework dedicated to the design, the analysis and the implementation of local search metaheuristics: ParadisEO-MO. A substantial number of single solution-based local search metaheuristics has been proposed so far, and an attempt of unifying existing approaches is here presented. Based on a fine-grained decomposition, a conceptual model is proposed and is validated by regarding a number of state-of-the-art methodologies as simple variants of the same structure. This model is then incorporated into the ParadisEO-MO software framework. This framework has proven its efficiency and high flexibility by enabling the resolution of many academic and real-world optimization problems from science and industry.
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Article dans une revue
Journal of Heuristics, Springer Verlag, 2013, 19 (6), pp.881-915. <10.1007/s10732-013-9228-8>
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https://hal.archives-ouvertes.fr/hal-00832029
Contributeur : Arnaud Liefooghe <>
Soumis le : lundi 10 juin 2013 - 07:46:08
Dernière modification le : samedi 16 janvier 2016 - 01:09:55

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Jérémie Humeau, Arnaud Liefooghe, El-Ghazali Talbi, Sébastien Verel. ParadisEO-MO: From Fitness Landscape Analysis to Efficient Local Search Algorithms. Journal of Heuristics, Springer Verlag, 2013, 19 (6), pp.881-915. <10.1007/s10732-013-9228-8>. <hal-00832029>

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