GPU-based Approaches for Multiobjective ...
Type de document :
Communication dans un congrès avec actes
Titre :
GPU-based Approaches for Multiobjective Local Search Algorithms. A Case Study: the Flowshop Scheduling Problem
Auteur(s) :
Luong, Thé Van [Auteur]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Melab, Nouredine [Auteur]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Talbi, El-Ghazali [Auteur]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Melab, Nouredine [Auteur]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Talbi, El-Ghazali [Auteur]

Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Éditeur(s) ou directeur(s) scientifique(s) :
Peter Merz and Jin-Kao Hao
Titre de la manifestation scientifique :
11th European Conference on Evolutionary Computation in Combinatorial Optimisation
Ville :
Torino
Pays :
Italie
Date de début de la manifestation scientifique :
2011
Titre de la revue :
Evolutionary Computation in Combinatorial Optimization - 11th European Conference, EvoCOP 2011, Torino, Italy, April 27-29, 2011. Proceedings
Éditeur :
Springer
Date de publication :
2011
Discipline(s) HAL :
Sciences cognitives/Informatique
Résumé en anglais : [en]
Multiobjective local search algorithms are efficient methods to solve complex problems in science and industry. Even if these heuristics allow to significantly reduce the computational time of the solution search space ...
Lire la suite >Multiobjective local search algorithms are efficient methods to solve complex problems in science and industry. Even if these heuristics allow to significantly reduce the computational time of the solution search space exploration, this latter cost remains exorbitant when very large problem instances are to be solved. As a result, the use of GPU computing has been recently revealed as an efficient way to accelerate the search process. This paper presents a new methodology to design and implement efficiently GPU-based multiobjective local search algorithms. The experimental results show that the approach is promising especially for large problem instances.Lire moins >
Lire la suite >Multiobjective local search algorithms are efficient methods to solve complex problems in science and industry. Even if these heuristics allow to significantly reduce the computational time of the solution search space exploration, this latter cost remains exorbitant when very large problem instances are to be solved. As a result, the use of GPU computing has been recently revealed as an efficient way to accelerate the search process. This paper presents a new methodology to design and implement efficiently GPU-based multiobjective local search algorithms. The experimental results show that the approach is promising especially for large problem instances.Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Collections :
Source :
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