Search and Optimization by Metaheuristics (PDF)
Techniques and Algorithms Inspired by Nature
(Sprache: Englisch)
This textbook provides a comprehensive introduction to nature-inspired metaheuristic methods for search and optimization, including the latest trends in evolutionary algorithms and other forms of natural computing. Over 100 different types of these methods...
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This textbook provides a comprehensive introduction to nature-inspired metaheuristic methods for search and optimization, including the latest trends in evolutionary algorithms and other forms of natural computing. Over 100 different types of these methods are discussed in detail. The authors emphasize non-standard optimization problems and utilize a natural approach to the topic, moving from basic notions to more complex ones.
Search and Optimization by Metaheuristics is intended primarily as a textbook for graduate and advanced undergraduate students specializing in engineering and computer science. It will also serve as a valuable resource for scientists and researchers working in these areas, as well as those who are interested in search and optimization methods.
Autoren-Porträt von Ke-Lin Du, M. N. S. Swamy
Ke-Lin Du, PhD, is Affiliate Associate Professor at Concordia University, Montreal, Quebec, Canada, and Founder and CEO of Xonlink Inc, Ningbo, China.M.N.S. Swamy, PhD, is Research Professor and Tier I Concordia Research Chair in the Department of Electrical and Computer Engineering at Concordia University, Montreal, Quebec, Canada.
Bibliographische Angaben
- Autoren: Ke-Lin Du , M. N. S. Swamy
- 2016, 1st ed. 2016, 434 Seiten, Englisch
- Verlag: Springer-Verlag GmbH
- ISBN-10: 3319411926
- ISBN-13: 9783319411927
- Erscheinungsdatum: 20.07.2016
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- Dateiformat: PDF
- Größe: 6.38 MB
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Englisch
Pressezitat
“The book under review contains large amount of precisely selected topics covering various aspects and design techniques related to efficient metaheuristic algorithms for searching and optimization. … is intended primarily as a textbook for graduate students specializing in engineering and computer science. Besides being very useful as a valuable resource for post-docs and researchers working in these areas, it may as well be used by those who are interested in search and optimization methods in general.” (Vladimír Lacko, zbMATH, 1351.90002, 2017)Kommentar zu "Search and Optimization by Metaheuristics"
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