Evolutionary and Swarm Intelligence Algorithms (Paperback, Softcover reprint of the original 1st ed. 2019)


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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Product Description

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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Product Details

General

Imprint

Springer Nature Switzerland AG

Country of origin

Switzerland

Series

Studies in Computational Intelligence, 779

Release date

2019

Availability

Expected to ship within 10 - 15 working days

First published

2019

Editors

, ,

Dimensions

235 x 155 x 11mm (L x W x T)

Format

Paperback

Pages

190

Edition

Softcover reprint of the original 1st ed. 2019

ISBN-13

978-3-03-008229-1

Barcode

9783030082291

Categories

LSN

3-03-008229-6



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