Advances in evolutionary algorithms : theory, design and practice
Genetic and evolutionary algorithms (GEAs) have often achieved an enviable success in solving optimization problems in a wide range of disciplines. The goal of this book is to provide effective optimization algorithms for solving a broad class of problems quickly, accurately, and reliably by employi...
Enregistré dans:
| Hovedforfatter: | |
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| Format: | Livre numérique |
| Sprog: | Anglais |
| Udgivet: |
Berlin ; Heidelberg :
Springer
[20..].
Cham : Springer Nature |
| Serier: | Studies in computational intelligence
vol. 18 Studies in Computational Intelligence 18 |
| Fag: | |
| Online adgang: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Kommentar: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Advances in Evolutionary Algorithms, Texte imprimé, 9783540317586 • Advances in Evolutionary Algorithms, Texte imprimé, 9783642068607 • Advances in Evolutionary Algorithms, Texte imprimé, 9783540820055 • Advances in Evolutionary Algorithms, Texte imprimé, 9783540317586 |
| Summary: | Genetic and evolutionary algorithms (GEAs) have often achieved an enviable success in solving optimization problems in a wide range of disciplines. The goal of this book is to provide effective optimization algorithms for solving a broad class of problems quickly, accurately, and reliably by employing evolutionary mechanisms. In this regard, five significant issues have been investigated: Bridging the gap between theory and practice of GEAs, thereby providing practical design guidelines. Demonstrating the practical use of the suggested road map. Offering a useful tool to significantly enhance the exploratory power in time-constrained and memory-limited applications. Providing a class of promising procedures that are capable of scalably solving hard problems in the continuous domain. Opening an important track for multiobjective GEA research that relies on decomposition principle. This book serves to play a decisive role in bringing forth a paradigm shift in future evolutionary computation |
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| Emne beskrivelse: | Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Bibliografi: | Bibliogr. p. [159]-166. Index |
| ISBN: | 3540317597 (en ligne) 9783540317593 |
| ISSN: | 1860-9503 |
| Adgang: | Accès en ligne pour les établissements français bénéficiaires des licences nationales Accès soumis à abonnement pour tout autre établissement Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 |