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Parallel fractal decomposition based ...
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Document type :
Article dans une revue scientifique
DOI :
10.1016/j.jpdc.2018.06.002
Title :
Parallel fractal decomposition based algorithm for big continuous optimization problems
Author(s) :
Nakib, Amir [Auteur]
SIMO
Souquet, Léo [Auteur]
Laboratoire Images, Signaux et Systèmes Intelligents [LISSI]
Talbi, El-Ghazali [Auteur]
Optimisation de grande taille et calcul large échelle [BONUS]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Journal title :
Journal of Parallel and Distributed Computing
Pages :
297-306
Publisher :
Elsevier
Publication date :
2019-11
ISSN :
0743-7315
English keyword(s) :
Very-large-scale optimization
Metaheuristics
Geometric fractal decomposition
Local search
Continuous optimization
HAL domain(s) :
Informatique [cs]/Intelligence artificielle [cs.AI]
English abstract : [en]
Fractal Decomposition Algorithm (FDA) is a metaheuristic that was recently proposed to solve high dimensional continuous optimization problems. This approach is based on a geometric fractal decomposition which divides the ...
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Fractal Decomposition Algorithm (FDA) is a metaheuristic that was recently proposed to solve high dimensional continuous optimization problems. This approach is based on a geometric fractal decomposition which divides the search space while looking for the optimal solution. While FDA and its fractal decomposition has shown to be an effective optimization algorithm, its running time grows significantly as the problems dimension increases. To overcome this expensive computational time, a parallelized version of FDA, called Parallel Fractal Decomposition Algorithm (PFDA) is proposed. The focus was on parallelizing the exploration and exploitation phases of the original algorithm on a multi-threaded environment. The performances of PFDA were evaluated on the same Benchmark used to illustrate FDA efficiency, the SOCO 2011. It is composed of 19 functions with dimensions going from 50 to 5000. Results show that PFDA reaches similar performances as the original version with a significantly reduced computational time.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Collections :
  • Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
Source :
Harvested from HAL
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