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Parallel cooperative meta-heuristics on ...
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Document type :
Article dans une revue scientifique
DOI :
10.1016/j.parco.2006.01.003
Title :
Parallel cooperative meta-heuristics on the computational grid. A case study: the bi-objective Flow-Shop problem
Author(s) :
Melab, Nouredine [Auteur]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Mezmaz, Mohand [Auteur]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Talbi, El-Ghazali [Auteur] refId
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Journal title :
Parallel Computing
Pages :
643-659
Publisher :
Elsevier
Publication date :
2006
ISSN :
0167-8191
HAL domain(s) :
Informatique [cs]/Autre [cs.OH]
English abstract : [en]
In this paper, we contribute with the first results on parallel cooperative multi-objective meta-heuristics on computational grids. We particularly focus on the island model and the multi-start model and their cooperation. ...
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In this paper, we contribute with the first results on parallel cooperative multi-objective meta-heuristics on computational grids. We particularly focus on the island model and the multi-start model and their cooperation. We propose a checkpointing-based approach to deal with the fault tolerance issue of the island model. Nowadays, existing Dispatcher- Worker grid middlewares are inadequate for the deployment of parallel cooperative applications. Indeed, these need to be extended with a software layer to support the cooperation. Therefore, we propose a Linda-like cooperation model and its implementation on top of XtremWeb. This middleware is then used to develop a parallel meta-heuristic applied to a bi-objective Flow-Shop problem using the two models. The work has been experimented on a multi-domain education network of 321 heterogeneous Linux PCs. The preliminary results, obtained after more than 10 days, demonstrate that the use of grid computing allows to fully exploit effectively different parallel models and their combination for solving large-size problem instances. An improvement of the effectiveness by over 60% is realized compared to serial metaheuristic.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 :
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