1st ed. 2021. XII, 404 p. Hardcover. Einband besto�en, daher M�ngelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Sprache: Englisch. N� de r�f. du vendeur 326NB

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Nature-Inspired Metaheuristic Algorithms for Engineering Optimization Applications (Springer Tracts in Nature-Inspired Computing)

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ISBN 10 : 9813367725 ISBN 13 : 9789813367722

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Nature-Inspired Metaheuristic Algorithms for Engineering Optimization Applications (Springer Tracts in Nature-Inspired Computing)

Edit� par Springer, 2021

ISBN 10 : 9813367725 ISBN 13 : 9789813367722

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Nature-Inspired Metaheuristic Algorithms for Engineering Optimization Applications

Carbas, Serdar|Toktas, Abdurrahim|Ustun, Deniz

Edit� par Springer Singapore, 2021

ISBN 10 : 9813367725 ISBN 13 : 9789813367722

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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents concise overviews of various nature-inspired metaheuristic algorithmsProvides solutions to specific engineering optimization problems with single and multi-objectivesServes as a reference for. N� de r�f. du vendeur 437752874

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Nature-Inspired Metaheuristic Algorithms for Engineering Optimization Applications

Serdar Carbas

Edit� par Springer Nature Singapore Apr 2021, 2021

ISBN 10 : 9813367725 ISBN 13 : 9789813367722

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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book engages in an ongoing topic, such as the implementation of nature-inspired metaheuristic algorithms, with a main concentration on optimization problems in different fields of engineering optimization applications. The chapters of the book provide concise overviews of various nature-inspired metaheuristic algorithms, defining their profits in obtaining the optimal solutions of tiresome engineering design problems that cannot be efficiently resolved via conventional mathematical-based techniques. Thus, the chapters report on advanced studies on the applications of not only the traditional, but also the contemporary certain nature-inspired metaheuristic algorithms to specific engineering optimization problems with single and multi-objectives. Harmony search, artificial bee colony, teaching learning-based optimization, electrostatic discharge, grasshopper, backtracking search, and interactive search are just some of the methods exhibited and consulted step by step in applicationcontexts. The book is a perfect guide for graduate students, researchers, academicians, and professionals willing to use metaheuristic algorithms in engineering optimization applications. 428 pp. Englisch. N� de r�f. du vendeur 9789813367722

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Nature-Inspired Metaheuristic Algorithms for Engineering Optimization Applications

Serdar Carbas

Edit� par Springer Nature Singapore, Springer Nature Singapore, 2021

ISBN 10 : 9813367725 ISBN 13 : 9789813367722

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Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne

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Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book engages in an ongoing topic, such as the implementation of nature-inspired metaheuristic algorithms, with a main concentration on optimization problems in different fields of engineering optimization applications. The chapters of the book provide concise overviews of various nature-inspired metaheuristic algorithms, defining their profits in obtaining the optimal solutions of tiresome engineering design problems that cannot be efficiently resolved via conventional mathematical-based techniques. Thus, the chapters report on advanced studies on the applications of not only the traditional, but also the contemporary certain nature-inspired metaheuristic algorithms to specific engineering optimization problems with single and multi-objectives. Harmony search, artificial bee colony, teaching learning-based optimization, electrostatic discharge, grasshopper, backtracking search, and interactive search are just some of the methods exhibited and consulted step by step in applicationcontexts. The book is a perfect guide for graduate students, researchers, academicians, and professionals willing to use metaheuristic algorithms in engineering optimization applications. N� de r�f. du vendeur 9789813367722

Contacter le vendeur