Evolutionary and Swarm Intelligence Algorithms

• Corporate Author: SpringerLink (Online service)
• Other Authors: Bansal, Jagdish Chand (Editor, http://id.loc.gov/vocabulary/relators/edt), Singh, Pramod Kumar (Editor, http://id.loc.gov/vocabulary/relators/edt), Pal, Nikhil R. (Editor, http://id.loc.gov/vocabulary/relators/edt)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2019.
• Edition: 1st ed. 2019.
• Series: Studies in Computational Intelligence, 779
• Subjects: Computational intelligence.; Artificial intelligence.; Computational Intelligence.; Artificial Intelligence.
• Physical Description: X, 190 p. 57 illus., 21 illus. in color. online resource.
• ISBN: 9783319913414
• ISSN: 1860-949X ;
• DOI: 10.1007/978-3-319-91341-4

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.