Foundations of Global Genetic Optimization
This book is devoted to the application of genetic algorithms in continuous global optimization. Some of their properties and behavior are highlighted and formally justified. Various optimization techniques and their taxonomy are the background for detailed discussion. The nature of continuous genet...
Zapisane w:
| 1. autor: | |
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| Format: | Livre numérique |
| Język: | Anglais |
| Wydane: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Wydanie: | 1st ed. 2007. |
| Seria: | Studies in Computational Intelligence
74 |
| Dostęp online: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Komentarz: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Foundations of global genetic optimization, Robert Schaefer, Berlin, Springer, 2007, 1 vol. (X-222 p.), Studies in computational intelligence, 978-3-540-73191-7 • Foundations of Global Genetic Optimization, Texte imprimé, 9783642092251 • Foundations of Global Genetic Optimization, Texte imprimé, 9783540839828 • Foundations of global genetic optimization, Robert Schaefer, Berlin, Springer, 2007, 1 vol. (X-222 p.), Studies in computational intelligence, 978-3-540-73191-7 |
| Streszczenie: | This book is devoted to the application of genetic algorithms in continuous global optimization. Some of their properties and behavior are highlighted and formally justified. Various optimization techniques and their taxonomy are the background for detailed discussion. The nature of continuous genetic search is explained by studying the dynamics of probabilistic measure, which is utilized to create subsequent populations. This approach shows that genetic algorithms can be used to extract some areas of the search domain more effectively than to find isolated local minima. The biological metaphor of such behavior is the whole population surviving by rapid exploration of new regions of feeding rather than caring for a single individual. One group of strategies that can make use of this property are two-phase global optimization methods. In the first phase the central parts of the basins of attraction are distinguished by genetic population analysis. Afterwards, the minimizers are found by convex optimization methods executed in parallel |
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| Deskrypcja: | Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| ISBN: | 9783540731924 |
| ISSN: | 1860-9503 |
| Ograniczenie dostępu: | 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 |