Skip to main content
SpringerLink
Log in

Using Fuzzy Logic Controller in Ant Colony Optimization

  • Conference paper
Artificial Intelligence Perspectives and Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 347))

Abstract

The new modification of ant colony optimization has been proposed to solve travelling salesman problem. This modification is based on using fuzzy rules and fuzzy terms like «a little», «much», «almost» etc. Fuzzy logic controller was developed to define fuzzy rules. This controller allows to regulate values of heuristic coefficients of ant colony optimization dynamically. Experimental research was carried out. The results received show high effectiveness of fuzzy logic controller using in ant colony optimization. The modified ant colony optimization algorithm finds shorter routes on 1-3%. This modification can be used to solve other problems.

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

Access this chapter

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

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Dorigo, M., Di Caro, G., Gambardella, L.M.: Ant Algorithms for discrete Optimizations. Artificial Life 2(5), 137–172 (1999)

    Article  Google Scholar 

  2. Kureichik, V.M., Kazharov, A.A., Lyapunova, I.A.: Parameter analysis of ant algorithm. Life Science Journal 2014 11(10s), 402–406 (2014)

    Google Scholar 

  3. Cristofides, N., Eilon, S.: An algorithm for the vehicle dispatching problem. Opl. Res. Quart. (1969)

    Google Scholar 

  4. Kazharov, A.A., Kureichik, V.M.: The Development of the Ant Algorithm for Solving the Vehicle Routing Problems. World Applied Sciences Journal 26(1), 114–121 (2013)

    Google Scholar 

  5. Jones, T.: AI Application Programming. Cengage Learning Press (2005)

    Google Scholar 

  6. Cormen, T.H., Leiserson, C.E., Rivest, R.L., Stein, C.: Introduction to Algorithms, 3rd edn. The MIT Press, Massachusetts (2009)

    MATH  Google Scholar 

  7. Stovba, S.D.: Ant algorithms. Exponents Pro. Mathematics in Application 4, 70–75 (2003)

    Google Scholar 

  8. Kazharov, A.A., Kureichik, V.M.: Ant colony optimization algorithms for solving transportation problems. Journal of Computer and Systems Sciences International 49(1), 30–43 (2010)

    Article  MATH  MathSciNet  Google Scholar 

  9. Liu, H., Xu, Z., Abraham, A.: Hybrid fuzzy-genetic algorithm approach for crew grouping. In: 5th International Conference on Intelligent Systems Design and Applications (ISDA 2005), pp. 332–337 (September 2005)

    Google Scholar 

  10. Cordon, O., Gomide, F., Herrera, F., Hoffmann, F., Magdalena, L.: Ten years of genetic fuzzy systems: current framework and new trends. Fuzzy Sets and Systems 141, 5–31 (2004)

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Chekhova St.,22, Taganrog, Russian Federation, 347928

    Victor M. Kureichik & Asker Kazharov

Authors
  1. Victor M. Kureichik
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Asker Kazharov
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Victor M. Kureichik .

Editor information

Editors and Affiliations

  1. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Radek Silhavy

  2. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Roman Senkerik

  3. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Zuzana Kominkova Oplatkova

  4. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Zdenka Prokopova

  5. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Petr Silhavy

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Kureichik, V.M., Kazharov, A. (2015). Using Fuzzy Logic Controller in Ant Colony Optimization. In: Silhavy, R., Senkerik, R., Oplatkova, Z., Prokopova, Z., Silhavy, P. (eds) Artificial Intelligence Perspectives and Applications. Advances in Intelligent Systems and Computing, vol 347. Springer, Cham. https://doi.org/10.1007/978-3-319-18476-0_16

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-18476-0_16

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-18475-3

  • Online ISBN: 978-3-319-18476-0

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation