Tornado: An Autonomous Chaotic Algorithm ...
Type de document :
Pré-publication ou Document de travail
Titre :
Tornado: An Autonomous Chaotic Algorithm for Large Scale Global Optimization
Auteur(s) :
Aslimani, Nassime [Auteur]
Optimisation de grande taille et calcul large échelle [BONUS]
Talbi, El-Ghazali [Auteur]
Optimisation de grande taille et calcul large échelle [BONUS]
Ellaia, Rachid [Auteur]
Laboratoire d'Etudes et Recherche en Mathématiques Appliquées [LERMA]
Optimisation de grande taille et calcul large échelle [BONUS]
Talbi, El-Ghazali [Auteur]
Optimisation de grande taille et calcul large échelle [BONUS]
Ellaia, Rachid [Auteur]
Laboratoire d'Etudes et Recherche en Mathématiques Appliquées [LERMA]
Mot(s)-clé(s) en anglais :
Levelling
Chaos optimization algorithm
Global optimization
Symmetrization
Fine search
Large scale optimization
Chaos optimization algorithm
Global optimization
Symmetrization
Fine search
Large scale optimization
Discipline(s) HAL :
Informatique [cs]
Informatique [cs]/Intelligence artificielle [cs.AI]
Informatique [cs]/Analyse numérique [cs.NA]
Informatique [cs]/Intelligence artificielle [cs.AI]
Informatique [cs]/Analyse numérique [cs.NA]
Résumé en anglais : [en]
In this paper we propose an autonomous chaotic optimization algorithm, called Tornado, for large scale global optimization problems. The algorithm introduces advanced symmetrization, levelling and fine search strategies ...
Lire la suite >In this paper we propose an autonomous chaotic optimization algorithm, called Tornado, for large scale global optimization problems. The algorithm introduces advanced symmetrization, levelling and fine search strategies for an efficient and effective exploration of the search space and exploitation of the best found solutions. To our knowledge, this is the first accurate and fast autonomous chaotic algorithm solving large scale optimization problems. A panel of various benchmark problems with different properties were used to assess the performance of the proposed chaotic algorithm. The obtained results has shown the scalability of the algorithm in contrast to chaotic optimization algorithms encountered in the literature. Moreover, in comparison with some state-of-the-art meta-heuristics (e.g. evolutionary algorithms, swarm intelligence), the computational results revealed that the proposed Tornado algorithm is an effective and efficient optimization algorithm.Lire moins >
Lire la suite >In this paper we propose an autonomous chaotic optimization algorithm, called Tornado, for large scale global optimization problems. The algorithm introduces advanced symmetrization, levelling and fine search strategies for an efficient and effective exploration of the search space and exploitation of the best found solutions. To our knowledge, this is the first accurate and fast autonomous chaotic algorithm solving large scale optimization problems. A panel of various benchmark problems with different properties were used to assess the performance of the proposed chaotic algorithm. The obtained results has shown the scalability of the algorithm in contrast to chaotic optimization algorithms encountered in the literature. Moreover, in comparison with some state-of-the-art meta-heuristics (e.g. evolutionary algorithms, swarm intelligence), the computational results revealed that the proposed Tornado algorithm is an effective and efficient optimization algorithm.Lire moins >
Langue :
Anglais
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