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Advanced Optimization by Nature-Inspired Algorithms [[electronic resource] /] / edited by Omid Bozorg-Haddad



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Titolo: Advanced Optimization by Nature-Inspired Algorithms [[electronic resource] /] / edited by Omid Bozorg-Haddad Visualizza cluster
Pubblicazione: Singapore : , : Springer Singapore : , : Imprint : Springer, , 2018
Edizione: 1st ed. 2018.
Descrizione fisica: 1 online resource (XV, 159 p. 34 illus., 4 illus. in color.)
Disciplina: 006.38
Soggetto topico: Computational intelligence
Mathematical optimization
Artificial intelligence
Operations research
Decision making
Mechanics
Mechanics, Applied
Optical data processing
Computational Intelligence
Optimization
Artificial Intelligence
Operations Research/Decision Theory
Theoretical and Applied Mechanics
Computer Imaging, Vision, Pattern Recognition and Graphics
Persona (resp. second.): Bozorg-HaddadOmid
Nota di bibliografia: Includes bibliographical references.
Nota di contenuto: Introduction -- Cat Swarm Optimization (CSO) Algorithm -- League Championship Algorithm (LCA) -- Anarchic Society Optimization (ASO) Algorithm -- Cuckoo Optimization Algorithm (COA) -- Teaching-Learning-Based Optimization (TLBO) Algorithm -- Flower pollination Algorithm (FPA) -- Krill Herd Algorithm (KHA) -- Grey Wolf Optimization (GWO) Algorithm -- Shark Smell Optimization (SSO) Algorithm -- Ant Lion Optimizer (ALO) Algorithm -- Gradient Evolution (GE) Algorithm -- Moth-Flame Optimization (MFO) Algorithm -- Crow Search Algorithm (CSA) -- Dragonfly Algorithm (DA).
Sommario/riassunto: This book, compiles, presents, and explains the most important meta-heuristic and evolutionary optimization algorithms whose successful performance has been proven in different fields of engineering, and it includes application of these algorithms to important engineering optimization problems. In addition, this book guides readers to studies that have implemented these algorithms by providing a literature review on developments and applications of each algorithm. This book is intended for students, but can be used by researchers and professionals in the area of engineering optimization.
Titolo autorizzato: Advanced Optimization by Nature-Inspired Algorithms  Visualizza cluster
ISBN: 981-10-5221-2
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910299569103321
Lo trovi qui: Univ. Federico II
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Serie: Studies in Computational Intelligence, . 1860-949X ; ; 720