Swarm Intelligence: Principles, Advances, and Applications delivers in-depth coverage of bat, artificial fish swarm, firefly, cuckoo search, flower pollination, artificial bee colony, wolf search, and gray wolf optimization algorithms. The book begins with a brief introduction to mathematical optimization, addressing basic concepts related to swarm intelligence, such as randomness, random walks, and chaos theory. The text then:Describes the various swarm intelligence optimization methods, standardizing the variants, hybridizations, and algorithms whenever possibleDiscusses variants that focus more on binary, discrete, constrained, adaptive, and chaotic versions of the swarm optimizersDepicts real-world applications of the individual optimizers, emphasizing variable selection and fitness function designDetails the similarities, differences, weaknesses, and strengths of each swarm optimization methodDraws parallels between the operators and searching manners of the different algorithms
Swarm Intelligence: Principles, Advances, and Applications presents a comprehensive treatment of modern swarm intelligence optimization methods, complete with illustrative examples and an extendable MATLAB ® package for feature selection in wrapper mode applied on different data sets with benchmarking using different evaluation criteria. The book provides beginners with a solid foundation of swarm intelligence fundamentals, and offers experts valuable insight into new directions and hybridizations.
Publisher: Taylor & Francis Inc
Number of pages: 210
Weight: 567 g
Dimensions: 254 x 178 x 18 mm
"The strength of this book lies in very new concepts, interesting and found diverse applications, in almost all field of science and technology... This book is very lucidly presented... The selection is very good."
-Dr. Mrutyunjaya Panda, Utkal University, Bhubaneswar, India