Algorithm configuration using GPU-based metaheuristics

Abstract : In this paper, a GPU-based implementation of Differential Evolution (DE) and Particle Swarm Optimization (PSO) in CUDA is used to automatically tune the parameters of PSO. The parameters were tuned over a set of 8 problems and then tested over 20 problems to assess the generalization ability of the tuners. We compare the results obtained using such parameters with the 'standard' ones proposed in the literature and the ones obtained by state-of-the-art tuning methods (irace). The results are comparable to the ones suggested for the standard version of PSO (SPSO), and the ones obtained by irace, while the GPU implementation makes tuning time acceptable. To the best of our knowledge, this is the first time that a general purpose library of GPU-based metaheuristics is used to solve this problem, as well as being one of the few cases where DE and PSO are both used as tuners.
Type de document :
Communication dans un congrès
15th Genetic and Evolutionary Computation Conference companion (GECCO’13), Jul 2013, Amsterdam, Netherlands. pp.221-222, 2013, 〈10.1145/2464576.2464682〉
Liste complète des métadonnées

Littérature citée [5 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/hal-01221570
Contributeur : Pablo Mesejo Santiago <>
Soumis le : mercredi 28 octobre 2015 - 11:35:12
Dernière modification le : jeudi 29 octobre 2015 - 01:08:55
Document(s) archivé(s) le : vendredi 29 janvier 2016 - 13:15:40

Fichier

gecco2pages_noCopyright.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

Collections

Citation

Roberto Ugolotti, Youssef S.G. Nashed, Pablo Mesejo, Stefano Cagnoni. Algorithm configuration using GPU-based metaheuristics. 15th Genetic and Evolutionary Computation Conference companion (GECCO’13), Jul 2013, Amsterdam, Netherlands. pp.221-222, 2013, 〈10.1145/2464576.2464682〉. 〈hal-01221570〉

Partager

Métriques

Consultations de la notice

53

Téléchargements de fichiers

77