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Handbook of Swarm Intelligence

Concepts, Principles and Applications

  • Bijaya Ketan Panigrahi
  • Yuhui Shi
  • Meng-Hiot Lim

Part of the Adaptation, Learning, and Optimization book series (ALO, volume 8)

Table of contents

  1. Front Matter
  2. Part A: Particle Swarm Optimization

    1. Front Matter
      Pages 1-1
    2. J. L. Fernández-Martínez, E. García-Gonzalo
      Pages 37-65
    3. Deepak Devicharan, Chilukuri K. Mohan
      Pages 119-132
    4. Sabine Helwig, Frank Neumann, Rolf Wanka
      Pages 155-173
    5. Zhihua Cui, Xingjuan Cai, Ying Tan, Jianchao Zeng
      Pages 175-199
    6. Zheng Zhang, Hock Soon Seah, Chee Kwang Quah
      Pages 201-220
    7. Praveen Kumar Tripathi, Sanghamitra Bandyopadhyay, Sankar Kumar Pal
      Pages 221-239
  3. Part B: Bee Colony Optimization

    1. Front Matter
      Pages 293-293
    2. Konrad Diwold, Madeleine Beekman, Martin Middendorf
      Pages 295-327
    3. Rafael Stubs Parpinelli, César Manuel Vargas Benitez, Heitor Silvério Lopes
      Pages 329-345
    4. Yannis Marinakis, Magdalene Marinaki
      Pages 347-369
  4. Part C: Ant Colony Optimization

    1. Front Matter
      Pages 371-371
    2. Oscar Castillo, Patricia Melin, Fevrier Valdez, Ricardo Martínez-Marroquín
      Pages 389-417
  5. Part D: Other Swarm Techniques

    1. Front Matter
      Pages 419-419
    2. Pei-Wei Tsai, Jeng-Shyang Pan, Peng Shi, Bin-Yih Liao
      Pages 421-449
    3. K. N. Krishnanand, D. Ghose
      Pages 451-467
    4. Ganapati Panda, Pyari Mohan Pradhan, Babita Majhi
      Pages 469-485
    5. S. S. Pattnaik, K. M. Bakwad, S. Devi, B. K. Panigrahi, Sanjoy Das
      Pages 487-502
    6. Leandro dos Santos Coelho, Diego L. de A. Bernert, Viviana Cocco Mariani
      Pages 503-516
    7. Debasish Datta, Amit Konar, Swagatam Das, B. K. Panigrahi
      Pages 517-542
  6. Back Matter

About this book

Introduction

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.

Keywords

Ant Colony Optimization Bacterial Foraging Harmony Search Particle Swarm Optimization Swarm Intelligence combinatorial problems multi-objective optimization single objective optimization

Editors and affiliations

  • Bijaya Ketan Panigrahi
    • 1
  • Yuhui Shi
    • 2
  • Meng-Hiot Lim
    • 3
  1. 1.Electrical Engineering DepartmentIndian Institute of Technology, Delhi New DelhiIndia
  2. 2.Director of Research and Postgraduate OfficeXi’an Jiaotong-Liverpool University SuzhouChina
  3. 3.School of Electrical & Electronic EngineeringNanyang Technological University Singapore

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-17390-5
  • Copyright Information Springer-Verlag Berlin Heidelberg 2011
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-642-17389-9
  • Online ISBN 978-3-642-17390-5
  • Series Print ISSN 1867-4534
  • Series Online ISSN 1867-4542
  • Buy this book on publisher's site