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Evolutionary and swarm intelligence algorithms

Title By: Bansal, Jagdish Chand [Edited by] | Singh, Pramod Kumar [Edited by] | Pal, Nikhil R [Edited by]
Material type: BookSeries: Studies in computational intelligence ; Vol. 779.Publisher: New York, NY : Springer, c2019.Description: x, 190 p. : ill. ; 25 cm.ISBN: 9783319913391Subject(s): Swarm intelligence | Evolutionary computationDDC classification: 006.3824 EV OL Online resources: Location Map
Summary:
This book is a delight for academics, researchers and professionals working in evolutionary and swarm computing, computational intelligence, machine learning and engineering design, as well as search and optimization in general. It provides an introduction to the design and development of a number of popular and recent swarm and evolutionary algorithms with a focus on their applications in engineering problems in diverse domains. The topics discussed include particle swarm optimization, the artificial bee colony algorithm, Spider Monkey optimization algorithm, genetic algorithms, constrained multi-objective evolutionary algorithms, genetic programming, and evolutionary fuzzy systems. A friendly and informative treatment of the topics makes this book an ideal reference for beginners and those with experience alike.
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Item type Home library Call number Status Notes Date due Barcode Item holds
REGULAR University of Wollongong in Dubai
Main Collection
006.3824 EV OL (Browse shelf) Available Mar2020 T0063590
Total holds: 0

This book is a delight for academics, researchers and professionals working in evolutionary and swarm computing, computational intelligence, machine learning and engineering design, as well as search and optimization in general. It provides an introduction to the design and development of a number of popular and recent swarm and evolutionary algorithms with a focus on their applications in engineering problems in diverse domains. The topics discussed include particle swarm optimization, the artificial bee colony algorithm, Spider Monkey optimization algorithm, genetic algorithms, constrained multi-objective evolutionary algorithms, genetic programming, and evolutionary fuzzy systems. A friendly and informative treatment of the topics makes this book an ideal reference for beginners and those with experience alike.

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