Adaptive and multilevel metaheuristics
One of the keystones in practical metaheuristic problem-solving is the fact that tuning the optimization technique to the problem under consideration is crucial for achieving top performance. This tuning/customization is usually in the hands of the algorithm designer, and despite some methodological...
محفوظ في:
| مؤلفون آخرون: | , , |
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| التنسيق: | Livre numérique |
| اللغة: | Anglais |
| منشور في: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| الطبعة: | 1st ed. 2008. |
| سلاسل: | Studies in Computational Intelligence
136 |
| الوصول للمادة أونلاين: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| ملاحظة: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Adaptive and Multilevel Metaheuristics, Texte imprimé, 9783540794370 • Adaptive and Multilevel Metaheuristics, Texte imprimé, 9783642098338 • Adaptive and Multilevel Metaheuristics, Texte imprimé, 9783540872344 • Adaptive and Multilevel Metaheuristics, Texte imprimé, 9783540794370 |
| الملخص: | One of the keystones in practical metaheuristic problem-solving is the fact that tuning the optimization technique to the problem under consideration is crucial for achieving top performance. This tuning/customization is usually in the hands of the algorithm designer, and despite some methodological attempts, it largely remains a scientific art. Transferring a part of this customization effort to the algorithm itself -endowing it with smart mechanisms to self-adapt to the problem- has been a long pursued goal in the field of metaheuristics. These mechanisms can involve different aspects of the algorithm, such as for example, self-adjusting the parameters, self-adapting the functioning of internal components, evolving search strategies, etc. Recently, the idea of hyperheuristics, i.e., using a metaheuristic layer for adapting the search by selectively using different low-level heuristics, has also been gaining popularity. This volume presents recent advances in the area of adaptativeness in metaheuristic optimization, including up-to-date reviews of hyperheuristics and self-adaptation in evolutionary algorithms, as well as cutting edge works on adaptive, self-adaptive and multilevel metaheuristics, with application to both combinatorial and continuous optimization |
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| وصف المادة: | Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| ردمك: | 9783540794387 |
| تدمد: | 1860-9503 |
| وصول: | 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 |