Articoli correlati a Multimodal Optimization by Means of Evolutionary Algorithms
Sinossi
This book offers the first comprehensive taxonomy for multimodal optimization algorithms, work with its root in topics such as niching, parallel evolutionary algorithms, and global optimization.
The author explains niching in evolutionary algorithms and its benefits; he examines their suitability for use as diagnostic tools for experimental analysis, especially for detecting problem (type) properties; and he measures and compares the performances of niching and canonical EAs using different benchmark test problem sets. His work consolidates the recent successes in this domain, presenting and explaining use cases, algorithms, and performance measures, with a focus throughout on the goals of the optimization processes and a deep understanding of the algorithms used.
The book will be useful for researchers and practitioners in the area of computational intelligence, particularly those engaged with heuristic search, multimodal optimization, evolutionary computing, and experimental analysis.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Recensione
“It provides an excellent explanation of the theoretical background of many topics in evolutionary computation ... . I strongly recommend this book for graduate students or any researcher who wants to work in the EC field ... . It also may help in improving some algorithms and may motivate the researcher to introduce new ones. ... the chapters are self-contained so that you can read individual chapters that you are interested in without the need to read the whole book.” (Nailah Al-Madi, Genetic Programming and Evolvable Machines, Vol. 17 (3), September, 2016)
L'autore
Dr. Mike Preuss got his Ph.D. in the Technische Universität Dortmund and he is now a researcher at the Westfälische Wilhelms-Universität Münster. He has published in the leading journals and conferences on various aspects of computational intelligence, in particular evolutionary computing, heuristics, search and multicriteria optimization and served on many of the key academic conference committees, journal boards and review committees in this field. He is a leading figure in the application of computational and artificial intelligence to games.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
- EditoreSpringer-Nature New York Inc
- Data di pubblicazione2015
- ISBN 10 3319074067
- ISBN 13 9783319074061
- RilegaturaCopertina rigida
- LinguaInglese
- Numero edizione1
- Numero di pagine190
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Multimodal Optimization by Means of Evolutionary Algorithms
Editore:
Springer International Publishing Dez 2015, 2015
ISBN 10: 3319074067
ISBN 13: 9783319074061
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book offers the first comprehensive taxonomy for multimodal optimization algorithms, work with its root in topics such as niching, parallel evolutionary algorithms, and global optimization. The author explains niching in evolutionary algorithms and its benefits; he examines their suitability for use as diagnostic tools for experimental analysis, especially for detecting problem (type) properties; and he measures and compares the performances of niching and canonical EAs using different benchmark test problem sets. His work consolidates the recent successes in this domain, presenting and explaining use cases, algorithms, and performance measures, with a focus throughout on the goals of the optimization processes and a deep understanding of the algorithms used. The book will be useful for researchers and practitioners in the area of computational intelligence, particularly those engaged with heuristic search, multimodal optimization, evolutionary computing, and experimental analysis. 212 pp. Englisch. Codice articolo 9783319074061
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Multimodal Optimization by Means of Evolutionary Algorithms
Editore:
Springer International Publishing, 2015
ISBN 10: 3319074067
ISBN 13: 9783319074061
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Da: AHA-BUCH GmbH, Einbeck, Germania
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Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book offers the first comprehensive taxonomy for multimodal optimization algorithms, work with its root in topics such as niching, parallel evolutionary algorithms, and global optimization. The author explains niching in evolutionary algorithms and its benefits; he examines their suitability for use as diagnostic tools for experimental analysis, especially for detecting problem (type) properties; and he measures and compares the performances of niching and canonical EAs using different benchmark test problem sets. His work consolidates the recent successes in this domain, presenting and explaining use cases, algorithms, and performance measures, with a focus throughout on the goals of the optimization processes and a deep understanding of the algorithms used. The book will be useful for researchers and practitioners in the area of computational intelligence, particularly those engaged with heuristic search, multimodal optimization, evolutionary computing, and experimental analysis. Codice articolo 9783319074061
Quantità: 1 disponibili
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Multimodal Optimization by Means of Evolutionary Algorithms
Editore:
Springer International Publishing, 2015
ISBN 10: 3319074067
ISBN 13: 9783319074061
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Da: moluna, Greven, Germania
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Describes state of the art in algorithms, measures and test problemsApproaches multimodal optimization algorithms via model-based simulation and statisticsValuable for practitioners with real-world black-box problemsDr. Mike Preuss got . Codice articolo 31558367
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Multimodal Optimization by Means of Evolutionary Algorithms (Natural Computing Series)
Da: Mispah books, Redhill, SURRE, Regno Unito
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Hardcover. Condizione: Like New. Like New. book. Codice articolo ERICA79733190740676
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