1st Edition

Swarm Intelligence
Principles, Advances, and Applications




ISBN 9781498741064
Published November 24, 2015 by CRC Press
210 Pages 25 B/W Illustrations

USD $115.00

Prices & shipping based on shipping country


Preview

Book Description

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
Sources of Inspiration
Random Variables
Pseudo-Random Number Generation
Random Walk
Chaos
Chapter Conclusion
Bibliography

Bat Algorithm
Bat Algorithm (BA)
BA Variants
Bat Hybridizations
BA in Real-World Applications
Chapter Conclusion
Bibliography

Artificial Fish Swarm Algorithm
Fish Swarm Optimization
Artificial Fish Swarm Algorithm (AFSA) Variants
AFSA Hybridizations
Fish Swarm in Real-World Applications
Chapter Conclusion
Bibliography

Cuckoo Search Algorithm
Cuckoo Search (CS)
CS Variants
CS Hybridizations
CS in Real-World Applications
Chapter Conclusion
Bibliography

Firefly Algorithm
Firefly Algorithm (FFA)
FFA Variant
FFA Hybridizations
Firefly in Real-World Applications
Chapter Conclusion
Bibliography

Flower Pollination Algorithm
Flower Pollination Algorithm (FPA)
FPA Variants
FPA: Hybridizations
Real-World Applications of the FPA
FPA in Feature Selection
Chapter Conclusion
Bibliography

Artificial Bee Colony Optimization
Artificial Bee Colony (ABC)
ABC Variants
ABC Hybridizations
ABC in Real-World Applications
Chapter Conclusion
Bibliography

Wolf-Based Search Algorithms
Wolf Search Algorithm (WSA)
Wolf Search Optimizers in Real-World Applications
Chapter Conclusion
Bibliography

Bird's-Eye View
Criteria (1) Classification According to Swarm Guide
Criteria (2) Classification According to the Probability Distribution Used
Criteria (3) Classification According to the Number of Behaviors Used
Criteria (4) Classification According to Exploitation of Positional Distribution of Agents
Criteria (5) Number of Control Parameters
Criteria (6) Classification According to Either Generation of Completely New Agents per Iteration
Criteria (7) Classification Based on Exploitation of Velocity Concept in the Optimization
Criteria (8) Classification According to the Type of Exploration/Exploitation Used
Chapter Conclusion

...
View More

Author(s)

Biography

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.

Reviews

"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