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Metaheuristic optimization : nature-inspired algorithms swarm and computational intelligence, theory and applications / / Modestus O. Okwu, Lagouge K. Tartibu



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Autore: Okwu Modestus O. Visualizza persona
Titolo: Metaheuristic optimization : nature-inspired algorithms swarm and computational intelligence, theory and applications / / Modestus O. Okwu, Lagouge K. Tartibu Visualizza cluster
Pubblicazione: Cham, Switzerland : , : Springer, , [2021]
©2021
Edizione: 1st ed. 2021.
Descrizione fisica: 1 online resource (XII, 192 p. 112 illus., 92 illus. in color.)
Disciplina: 006.3
Soggetto topico: Computational intelligence
Metaheuristics
Persona (resp. second.): TartibuLagouge K.
Nota di bibliografia: Includes bibliographical references.
Nota di contenuto: Introduction To Optimization -- Particle Swarm Optimisation -- Artificial Bee Colony Algorithm -- Ant Colony Algorithm -- Grey Wolf Optimizer -- Whale Optimization Algorithm -- Bat Algorithm -- Ant Lion Optimization Algorithm -- Grasshopper Optimisation Algorithm (Goa) -- Moths–Flame Optimization Algorithm -- Genetic Algorithm -- Artificial Neural Network -- Future of Nature Inspired Algorithm, Swarm and Computational Intelligence.
Sommario/riassunto: This book exemplifies how algorithms are developed by mimicking nature. Classical techniques for solving day-to-day problems is time-consuming and cannot address complex problems. Metaheuristic algorithms are nature-inspired optimization techniques for solving real-life complex problems. This book emphasizes the social behaviour of insects, animals and other natural entities, in terms of converging power and benefits. Major nature-inspired algorithms discussed in this book include the bee colony algorithm, ant colony algorithm, grey wolf optimization algorithm, whale optimization algorithm, firefly algorithm, bat algorithm, ant lion optimization algorithm, grasshopper optimization algorithm, butterfly optimization algorithm and others. The algorithms have been arranged in chapters to help readers gain better insight into nature-inspired systems and swarm intelligence. All the MATLAB codes have been provided in the appendices of the book to enable readers practice how to solve examples included in all sections. This book is for experts in Engineering and Applied Sciences, Natural and Formal Sciences, Economics, Humanities and Social Sciences.
Titolo autorizzato: Metaheuristic optimization  Visualizza cluster
ISBN: 3-030-61111-6
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910484517103321
Lo trovi qui: Univ. Federico II
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Serie: Studies in computational intelligence ; ; Volume 927.