Swarm Intelligence

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

  1. Front Cover
  2. Contents (1/2)
  3. Contents (2/2)
  4. List of Figures
  5. List of Tables
  6. Preface
  7. 1. Introduction (1/3)
  8. 1. Introduction (2/3)
  9. 1. Introduction (3/3)
  10. 2. Bat Algorithm (BA) (1/6)
  11. 2. Bat Algorithm (BA) (2/6)
  12. 2. Bat Algorithm (BA) (3/6)
  13. 2. Bat Algorithm (BA) (4/6)
  14. 2. Bat Algorithm (BA) (5/6)
  15. 2. Bat Algorithm (BA) (6/6)
  16. 3. Artificial Fish Swarm (1/5)
  17. 3. Artificial Fish Swarm (2/5)
  18. 3. Artificial Fish Swarm (3/5)
  19. 3. Artificial Fish Swarm (4/5)
  20. 3. Artificial Fish Swarm (5/5)
  21. 4. Cuckoo Search Algorithm (1/5)
  22. 4. Cuckoo Search Algorithm (2/5)
  23. 4. Cuckoo Search Algorithm (3/5)
  24. 4. Cuckoo Search Algorithm (4/5)
  25. 4. Cuckoo Search Algorithm (5/5)
  26. 5. Firefly Algorithm (FFA) (1/6)
  27. 5. Firefly Algorithm (FFA) (2/6)
  28. 5. Firefly Algorithm (FFA) (3/6)
  29. 5. Firefly Algorithm (FFA) (4/6)
  30. 5. Firefly Algorithm (FFA) (5/6)
  31. 5. Firefly Algorithm (FFA) (6/6)
  32. 6. Flower Pollination Algorithm (1/3)
  33. 6. Flower Pollination Algorithm (2/3)
  34. 6. Flower Pollination Algorithm (3/3)
  35. 7. Artificial Bee Colony Optimization (1/8)
  36. 7. Artificial Bee Colony Optimization (2/8)
  37. 7. Artificial Bee Colony Optimization (3/8)
  38. 7. Artificial Bee Colony Optimization (4/8)
  39. 7. Artificial Bee Colony Optimization (5/8)
  40. 7. Artificial Bee Colony Optimization (6/8)
  41. 7. Artificial Bee Colony Optimization (7/8)
  42. 7. Artificial Bee Colony Optimization (8/8)
  43. 8. Wolf-Based Search Algorithms (1/3)
  44. 8. Wolf-Based Search Algorithms (2/3)
  45. 8. Wolf-Based Search Algorithms (3/3)
  46. 9. Bird's-Eye View (1/3)
  47. 9. Bird's-Eye View (2/3)
  48. 9. Bird's-Eye View (3/3)
  49. Back Cover

Product information

  • Title: Swarm Intelligence
  • Author(s): Aboul Ella Hassanien, Eid Emary
  • Release date: September 2018
  • Publisher(s): CRC Press
  • ISBN: 9781498741071