
Evolutionary and Swarm Intelligence Algorithms
Springer (Publisher)
Published on 26. January 2019
Book
Paperback/Softback
X, 190 pages
978-3-030-08229-1 (ISBN)
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.
More details
Series
Edition
Softcover Reprint of the Original 1st 2019 ed.
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
36 s/w Abbildungen, 21 farbige Abbildungen
X, 190 p. 57 illus., 21 illus. in color.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 12 mm
Weight
312 gr
ISBN-13
978-3-030-08229-1 (9783030082291)
DOI
10.1007/978-3-319-91341-4
Schweitzer Classification
Other editions
Additional editions

Jagdish Chand Bansal | Pramod Kumar Singh | Nikhil R. Pal
Evolutionary and Swarm Intelligence Algorithms
Book
06/2018
Springer
€149.79
Shipment within 10-15 days
Content
Swarm and Evolutionary Computation.- Particle Swarm Optimization.- Artificial Bee Colony Algorithm Variants and Its Application to Colormap Quantization.- Spider Monkey Optimization Algorithm.- Genetic Algorithm and Its Advances in Embracing Memetics.- Constrained Multi-Objective Evolutionary Algorithm.- Genetic Programming for Classification and Feature Selection.- Genetic Programming for Job Shop Scheduling.- Evolutionary Fuzzy Systems: A Case Study for Intrusion Detection Systems.