Skip to main content
SpringerLink
Log in
Book cover

Innovations in Swarm Intelligence pp 1–7Cite as

Advances in Swarm Intelligence

  • Chapter

Part of the book series: Studies in Computational Intelligence ((SCI,volume 248))

Abstract

In this chapter, advances in techniques and applications of swarm intelligence are presented. An overview of different swarm intelligence models is described. The dynamics of each swarm intelligence model and the associated characteristics in solving optimization as well as other problems are explained. The application and implementation of swarm intelligence in a variety of different domains are discussed. The contribution of each chapter included in this book is also highlighted.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Grosan, C., Abraham, A., Monica, C.: Swarm Intelligence in Data Mining. In: Abraham, A., Grosan, C., Ramos, V. (eds.) Swarm Intelligence in Data Mining. SCI, vol. 34, pp. 1–16. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  2. Colorni, A., Dorigo, M., Maniezzo, V.: Distributed Optimization by Ant Colonies. In: Varela, F., Bourgine, P. (eds.) Proceedings of the First European Conference on Artifical Life, pp. 134–142. MIT Press, Cambridge (1992)

    Google Scholar 

  3. Dorigo, M., Maniezzo, V., Colorni, A.: The Ant System: Optimization by a Colony of Cooperating Agents. IEEE Transactions on Systems, Man, and Cybernetics 26, 29–41 (1996)

    Article  Google Scholar 

  4. Kennedy, J., Eberhart, R.: Particle Swarm Optimization. In: Proceedings of IEEE International Conference on Neural Networks, vol. 4, pp. 1942–1948 (1995)

    Google Scholar 

  5. del Valle, Y., Venayagamoorthy, G.K., Mohaghenghi, S., Hernandez, J.C., Harley, R.G.: Particle Swarm Optimization: Basic Concepts, Variants and Applications in Power Systems. IEEE Transactions on Evolutionary Computation 12, 171–195 (2008)

    Article  Google Scholar 

  6. Seeley, T.D.: The Wisdom of the Hive. Harward University Press (1996)

    Google Scholar 

  7. Teodorovic, D., Dell’orco, M.: Bee Colony Optimization-A Cooperative Learning Approach to Complex Transportation Problems, Advanced OR and AI Methods in Transportation, pp. 51–60 (2005)

    Google Scholar 

  8. Passino, K.M.: Distributed Optimization and Control Using Only a Germ of Intelligence. In: Proceedings of the 2000 IEEE International Symposium on Intelligent Control, pp. 5–13 (2000)

    Google Scholar 

  9. Passino, K.M.: Biomimicry of Bacteria Foraging for Distributed Optimization and Control. IEEE Control Systems Magazine 22, 52–67 (2002)

    Article  Google Scholar 

  10. Venayagamoorthy, G.K., Harley, R.G.: Swarm Intelligence for Transmission System Control. In: IEEE Power Engineering Society General Meeting, pp. 1–4 (2007)

    Google Scholar 

  11. Kennedy, J., Eberhart, R.C.: Swarm Intelligence. Morgan Kaufmann Publisher, San Francisco (2001)

    Google Scholar 

  12. Bai, H., Zhao, B.: A Survey on Application of Swarm Intelligence Computation to Electric Power System. In: Proceedings of the 6th World Congress on Intelligent Control and Automation, vol. 2, pp. 7587–7591 (2006)

    Google Scholar 

  13. Bonabeau, E., Dorigo, M., Theraulaz, G.: Inspiration for Optimization from Social Insect Behavior. Nature 406, 39–42 (2002)

    Article  Google Scholar 

  14. Millonas, M.: Swarms, Phase Transitions, and Collective Intelligence. In: Langton, C.G. (ed.) Artificial Life III, vol. XVII, pp. 417–445. Addison-Wesley Publishing Company, Reading (1994)

    Google Scholar 

  15. Dorigo, M., Gambardella, L.M.: Ant Colonies for the Traveling Salesman Problem. ByoSystems 43, 73–81 (1997)

    Article  Google Scholar 

  16. Stutzle, T., Hoos, H.: The MAX–MIN Ant System and Local Search for the Traveling Salesman Problem. In: Angeline, P. (ed.) Proceedings of the IEEE International Conference on Evolutionary Computation, pp. 308–313. Springer, Heidelberg (1997)

    Google Scholar 

  17. Clerc, M., Kennedy, J.: The Particle Swarm: Explosion, Stability, and Convergence in a Multi-dimensional Complex Space. IEEE Transactions on Evolutionary Computation 6, 58–73 (2002)

    Article  Google Scholar 

  18. Mendes, R., Kennedy, J., Neves, J.: The Fully Informed Particle Swarm: Simpler, may be Better. IEEE Transactions on Evolutionary Computation 8, 204–210 (2004)

    Article  Google Scholar 

  19. von Frisch, K.: Decoding the Language of the Bee. Science 185, 663–668 (1974)

    Article  Google Scholar 

  20. Subbotina, S.A., Oleinik, A.A.: Multiagent Optimizaiton based on the Bee-Colony Method. Cybernetics and Systems Analysis 45, 177–186 (2009)

    Article  Google Scholar 

  21. Yang, X.S.: Engineering Optimizations via Nature-Inspired Virtual Bee Algorithms. In: Mira, J., Álvarez, J.R. (eds.) IWINAC 2005. LNCS, vol. 3562, pp. 317–323. Springer, Heidelberg (2005)

    Google Scholar 

  22. Das, S., Abraham, A., Konar, A.: Swarm Intelligence Algorithms in Bioinformatics. In: Kelemen, A., Abraham, A., Chen, Y. (eds.) Computational Intelligence in Bioinformatics, pp. 113–147. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  23. Lucic, P., Teodorovic, D.: Computing with Bees: Attacking Complex Transportation Engineering Problems. International Journal on Artificial Intelligence Tools 12, 375–394 (2003)

    Article  Google Scholar 

  24. Teodorovic, D., Lucic, P., Markovic, G., Dell’ Orco, M.: Bee Colony Optimization: Principles andApplications. In: Proceedings of the 8th Seminar on Neural Network Applications in Electrical Engineering, pp. 151–156 (2006)

    Google Scholar 

  25. Wong, L.P., Puan, C.Y., Low, M.Y.H., Chong, C.S.: Bee Colony Optimization Algorithm with Big Valley Landscape Exploitation for Job Shop Scheduling Problems. In: Proceedings of the 40th Conference on Winder Simulation, pp. 2050–2058 (2008)

    Google Scholar 

  26. Baykasoglu, A., Özbakır, L., Tapkan, P.: Artificial Bee Colony Algorithm and Its Application to Generalized Assignment Problem. Intelligence. In: Chan, F.T.S., Tiwari, M.K. (eds.) Swarm Intelligence: Focus on Ant and Particle Swarm Optimization, pp. 532–564. Itech Education and Publishing, Vienna (2007)

    Google Scholar 

  27. Duan, H., Yu, X.: Progresses and Challenges of Ant Colony Optimization-Based Evolvable Hardware. In: Proceedings of the 2007 IEEE Workshop on Evolvable and Adaptive Hardware, pp. 67–71 (2007)

    Google Scholar 

  28. Johnson, C., Venayagamoorthy, G.K., Palangpour, P.: Hardware Implementations of Swarming Intelligence–A Survey. In: Proceedings of the 2008 IEEE Swarm Intelligence Symposium, pp. 1–9 (2008)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Electrical & Information Engineering, University of South Australia, Australia

    Chee Peng Lim & Lakhmi C. Jain

Authors
  1. Chee Peng Lim
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lakhmi C. Jain
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. University of South Australia, Adelaide, Australia

    Chee Peng Lim  & Lakhmi C. Jain  & 

  2. Soft Computing Laboratory, Department of computer Science, Yonsei University, 120-749, Seoul, Korea

    Satchidananda Dehuri

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Lim, C.P., Jain, L.C. (2009). Advances in Swarm Intelligence. In: Lim, C.P., Jain, L.C., Dehuri, S. (eds) Innovations in Swarm Intelligence. Studies in Computational Intelligence, vol 248. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04225-6_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-04225-6_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04224-9

  • Online ISBN: 978-3-642-04225-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation