Neighborhood Structures for GPU-based Local Search Algorithms

Luong, Thé Van; Melab, Nouredine; Talbi, El-Ghazali

Type de document :

Compte-rendu et recension critique d'ouvrage

DOI :

10.1142/S0129626410000260

Titre :

Neighborhood Structures for GPU-based Local Search Algorithms

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]

Titre de la revue :

Parallel Processing Letters

Pagination :

307-324

Éditeur :

World Scientific Publishing

Date de publication :

2010

ISSN :

0129-6264

Mot(s)-clé(s) en anglais :

GPU-based metaheuristics
Parallel local search algorithms on GPU

Discipline(s) HAL :

Informatique [cs]/Autre [cs.OH]

Résumé en anglais : [en]

Local search algorithms are powerful heuristics for solving computationally hard problems in science and industry. In these methods, designing neighborhood operators to explore large promising regions of the search space ...
Lire la suite >Local search algorithms are powerful heuristics for solving computationally hard problems in science and industry. In these methods, designing neighborhood operators to explore large promising regions of the search space may improve the quality of the obtained solutions at the expense of a high computation process. As a consequence, the use of GPU computing provides an efficient way to speed up the search. However, designing applications on GPU is still complex and many issues have to be faced. We provide a methodology to design and implement different neighborhood structures for LS algorithms on GPU. The work has been evaluated for binary problems and the obtained results are convincing both in terms of efficiency, quality and robustness of the provided solutions at run time.Lire moins >

Langue :

Anglais

Vulgarisation :

Non

Collections :