Adaptive differential evolution : a robust approach to multimodal problem optimization

Optimization problems are ubiquitous in academic research and real-world applications wherever such resources as space, time and cost are limited. Researchers and practitioners need to solve problems fundamental to their daily work which, however, may show a variety of challenging characteristics su...

Description complète

Enregistré dans:
Détails bibliographiques
Auteurs principaux: Zhang, Jingqiao, Sanderson, Arthur C. (Auteur)
Format: Livre numérique
Langue:Anglais
Publié: Berlin, Heidelberg : Springer Berlin Heidelberg [20..].
Cham : Springer Nature
Édition:1st ed. 2009.
Collection:Evolutionary Learning and Optimization 1
Accès en ligne:Accès sur la plateforme de l'éditeur
Accès sur la plateforme Istex
Accès Université d'Orléans
Accès INSA CVL
Note: Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
Autres localisations: Voir dans le Sudoc
Edition sous un autre format:• Adaptive Differential Evolution, Texte imprimé, 9783642015267
• Adaptive Differential Evolution, Texte imprimé, 9783642015281
• Adaptive Differential Evolution, Texte imprimé, 9783642015267
• Adaptive Differential Evolution, Texte imprimé, 9783642260216
• Adaptive Differential Evolution, Texte imprimé, 9783642015281
• Adaptive Differential Evolution, Texte imprimé, 9783642015267
• Adaptive Differential Evolution, Texte imprimé, 9783642260216
Table des matières:
  • Related Work and Background Theoretical Analysis of Differential Evolution Parameter Adaptive Differential Evolution Surrogate Model-Based Differential Evolution Adaptive Multi-objective Differential Evolution Application to Winner Determination Problems in Combinatorial Auctions Application to Flight Planning in Air Traffic Control Systems Application to the TPM Optimization in Credit Decision Making Conclusions and Future Work