ParadisEO-MOEO: A Framework for Evolutionary Multi-objective Optimization

Abstract : This paper presents ParadisEO-MOEO, a white-box object-oriented generic framework dedicated to the flexible design of evolutionary multi-objective algorithms. This paradigm-free software embeds some features and techniques for Pareto-based resolution and aims to provide a set of classes allowing to ease and speed up the development of computationally efficient programs. 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). 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. In addition, GUIMOO, a platform-independant free software dedicated to results analysis for multi-objective problems, is briefly introduced.
Type de document :
Communication dans un congrès
Evolutionary Multi-Criterion Optimization (EMO 2007), Feb 2007, Matsushima, Japan. 4403, pp.386-400, 2007, Lecture Notes in Computer Science (LNCS). 〈10.1007/978-3-540-70928-2_31〉
Liste complète des métadonnées

Littérature citée [24 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/inria-00269972
Contributeur : Arnaud Liefooghe <>
Soumis le : jeudi 3 avril 2008 - 13:42:08
Dernière modification le : vendredi 28 septembre 2018 - 16:18:07
Document(s) archivé(s) le : vendredi 21 mai 2010 - 01:17:34

Fichier

075.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

Citation

Arnaud Liefooghe, Matthieu Basseur, Laetitia Jourdan, El-Ghazali Talbi. ParadisEO-MOEO: A Framework for Evolutionary Multi-objective Optimization. Evolutionary Multi-Criterion Optimization (EMO 2007), Feb 2007, Matsushima, Japan. 4403, pp.386-400, 2007, Lecture Notes in Computer Science (LNCS). 〈10.1007/978-3-540-70928-2_31〉. 〈inria-00269972〉

Partager

Métriques

Consultations de la notice

604

Téléchargements de fichiers

469