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 possible
- Discusses variants that focus more on binary, discrete, constrained, adaptive, and chaotic versions of the swarm optimizers
- Depicts real-world applications of the individual optimizers, emphasizing variable selection and fitness function design
- Details the similarities, differences, weaknesses, and strengths of each swarm optimization method
- Draws 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.
Table of Contents
Introduction. Bat Algorithm. Artificial Fish Swarm Algorithm. Cuckoo Search Algorithm. Firefly Algorithm. Flower Pollination Algorithm. Artificial Bee Colony Optimization. Wolf-Based Search Algorithms. Bird's-Eye View.
Aboul Ella Hassanien is a full professor in the Information Technology Department of the Faculty of Computers and Information at Cairo University, Giza, Egypt. Widely published and highly decorated, he is the founder and chair of the Scientific Research Group in Egypt, has established the Egyptian Rough Sets Society, and is chairing the Egyptian International Rough Set Society Chapter. He has served as a general chair, co-chair, program chair, and program committee member of various international conferences, and as a reviewer and guest editor for numerous international journals. His research interests include computational intelligence, network security, animal identification, and more.
Eid Emary is currently a lecturer in the Information Technology Department of the Faculty of Computers and Information at Cairo University, Giza, Egypt. He has authored or co-authored more than 15 research publications in peer-reviewed journals, book chapters, and conference proceedings. He has served as a technical program committee member of various international conferences, and as a reviewer for numerous international journals. His research interests are in the areas of computer vision, mathematical optimization, pattern recognition, video and image processing, machine learning, data mining, and biometrics.
"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