Computational Intelligence in Expensive Optimization Problems
In modern science and engineering, laboratory experiments are replaced by high fidelity and computationally expensive simulations. Using such simulations reduces costs and shortens development times but introduces new challenges to design optimization process. Examples of such challenges include lim...
Guardat en:
| Altres autors: | , |
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| Format: | Livre numérique |
| Idioma: | Anglais |
| Publicat: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Col·lecció: | Evolutionary Learning and Optimization
2 Adaptation Learning and Optimization 2 |
| Accés en línia: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Nota: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Computational intelligence in expensive optimization problems, Yoel Tenne, Chi-Keong Goh, (Eds), Berlin, Springer, 2010, 1 vol. (XXIX- 723 p.), Adaptation, learning, and optimization, 978-3-642-10700-9 |
| Sumari: | In modern science and engineering, laboratory experiments are replaced by high fidelity and computationally expensive simulations. Using such simulations reduces costs and shortens development times but introduces new challenges to design optimization process. Examples of such challenges include limited computational resource for simulation runs, complicated response surface of the simulation inputs-outputs, and etc. Under such difficulties, classical optimization and analysis methods may perform poorly. This motivates the application of computational intelligence methods such as evolutionary algorithms, neural networks and fuzzy logic, which often perform well in such settings. This is the first book to introduce the emerging field of computational intelligence in expensive optimization problems. Topics covered include: Dedicated implementations of evolutionary algorithms, neural networks and fuzzy logic. Reduction of expensive evaluations (modelling, variable-fidelity, fitness inheritance). Frameworks for optimization (model management, complexity control, model selection). Parallelization of algorithms (implementation issues on clusters, grids, parallel machines). Incorporation of expert systems and human-system interface. Single and multiobjective algorithms. Data mining and statistical analysis. Analysis of real-world cases (such as multidisciplinary design optimization). The edited book provides both theoretical treatments and real-world insights gained by experience, all contributed by leading researchers in the respective fields. As such, it is a comprehensive reference for researchers, practitioners, and advanced-level students interested in both the theory and practice of using computational intelligence for expensive optimization problems |
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| Descripció de l’ítem: | Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| ISBN: | 9783642107016 |
| ISSN: | 1867-4542 |
| Accés: | 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 |