Adaptation, Learning, and Optimization

Handbook of Swarm Intelligence

Concepts, Principles and Applications

Editors: Panigrahi, Bijaya Ketan, Shi, Yuhui, Lim, Meng-Hiot (Eds.)

  • Comprehensive study of both theoretical and algorithmic analysis of swarm intelligence techniques
  • Provides real-world applications of SI techniques
  • Written by leading experts in the field
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  • ISBN 978-3-642-26689-8
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About this book

From nature, we observe swarming behavior in the form of ant colonies, bird flocking, animal herding, honey bees, swarming of bacteria, and many more.  It is only in recent years that researchers have taken notice of such natural swarming systems as culmination of some form of innate collective intelligence, albeit swarm intelligence (SI) - a metaphor that inspires a myriad of computational problem-solving techniques.  In computational intelligence, swarm-like algorithms have been successfully applied to solve many real-world problems in engineering and sciences. This handbook volume serves as a useful foundational as well as consolidatory state-of-art collection of articles in the field from various researchers around the globe.  It has a rich collection of contributions pertaining to the theoretical and empirical study of single and multi-objective variants of swarm intelligence based algorithms like particle swarm optimization (PSO), ant colony optimization (ACO), bacterial foraging optimization algorithm (BFOA), honey bee social foraging algorithms, and harmony search (HS).  With chapters describing various applications of SI techniques in real-world engineering problems, this handbook can be a valuable resource for researchers and practitioners, giving an in-depth flavor of what SI is capable of achieving.

Table of contents (23 chapters)

  • From Theory to Practice in Particle Swarm Optimization

    Clerc, Maurice

    Pages 3-36

  • What Makes Particle Swarm Optimization a Very Interesting and Powerful Algorithm?

    Fernández-Martínez, J. L. (et al.)

    Pages 37-65

  • Developing Niching Algorithms in Particle Swarm Optimization

    Li, Xiaodong

    Pages 67-88

  • Test Function Generators for Assessing the Performance of PSO Algorithms in Multimodal Optimization

    Barrera, Julio (et al.)

    Pages 89-117

  • Linkage Sensitive Particle Swarm Optimization

    Devicharan, Deepak (et al.)

    Pages 119-132

Buy this book

eBook $259.00
price for USA (gross)
  • ISBN 978-3-642-17390-5
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $329.00
price for USA
  • ISBN 978-3-642-17389-9
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $329.00
price for USA
  • ISBN 978-3-642-26689-8
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Rent the ebook  
  • Rental duration: 1 or 6 month
  • low-cost access
  • online reader with highlighting and note-making option
  • can be used across all devices
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Bibliographic Information

Bibliographic Information
Book Title
Handbook of Swarm Intelligence
Book Subtitle
Concepts, Principles and Applications
Editors
  • Bijaya Ketan Panigrahi
  • Yuhui Shi
  • Meng-Hiot Lim
Series Title
Adaptation, Learning, and Optimization
Series Volume
8
Copyright
2011
Publisher
Springer-Verlag Berlin Heidelberg
Copyright Holder
Springer-Verlag Berlin Heidelberg
eBook ISBN
978-3-642-17390-5
DOI
10.1007/978-3-642-17390-5
Hardcover ISBN
978-3-642-17389-9
Softcover ISBN
978-3-642-26689-8
Series ISSN
1867-4534
Edition Number
1
Number of Pages
XII, 544
Topics