Skip to main content
SpringerLink
Log in

Multi-Colony Ant Algorithm Using a Sociometry-Based Network and Its Application

  • Conference paper
  • First Online:
Advances in Swarm and Computational Intelligence (ICSI 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9140))

Included in the following conference series:

Abstract

In this paper, the social fabric approach is weaved into multi-behavior based multi-colony ant colony system (MBMC-ACS) to construct pheromone diffusion model. According to the propagation characteristics of knowledge in the social fabric, the Cobb-Dauglas production function is introduced to describe the increase of pheromone caused by pheromone diffusion. The pheromone diffused inter-colonies based on sociometry-based networks can simulate the knowledge evolution mechanism in organizational learning network, which allows the algorithm to avoid premature convergence and stagnation problems. The experimental results for TSP show the validity of this algorithm.

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 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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.

References

  1. Bonabeau, E., Dorigo, M., Theraulaz, G.: Swarm Intelligence: From Natural to Artificial Systems. Oxford University Press, New York (1999)

    MATH  Google Scholar 

  2. Dorigo, M., Gambardella, L.M.: Ant colony system: A cooperative learning approach to the traveling salesman problem. IEEE Transaction on Evolutionary Computation 1(1), 53–66 (1997)

    Article  Google Scholar 

  3. Liao, K., Socha, M., Montes de Oca, M.A., Stützle, T., Dorigo, M.: Ant Colony Optimization for Mixed-Variable Optimization Problems. IEEE Transactions on Evolutionary Computation 18(4), 503–518 (2014)

    Article  Google Scholar 

  4. Iacopino, C., Palmer, P.: The dynamics of ant colony optimization algorithms applied to binary chains. Swarm Intelligence 6(4), 343–377 (2012)

    Article  Google Scholar 

  5. Iacopino, C., Palmer, P., et al.: A novel ACO algorithm for dynamic binary chains based on changes in the system’s stability. In: 2013 IEEE Symposium on Swarm Intelligence, pp. 56–63 (2013)

    Google Scholar 

  6. Liu, S., You, X.M.: On Multi-Behavior Based Multi-Colony Ant Algorithm for TSP. IEEE Computer Society, 2009.11

    Google Scholar 

  7. Mostafa, Z.A., Ayad, S., Randa Snanieh, T.A., Reynolds, R.G.: Boosting cultural algorithms with an incongruous layered social fabric influence function. In: IEEE Congress on Evolutionary Computation, pp. 1225–1232 (2011)

    Google Scholar 

  8. Lizárraga, E., Castillo, O., Soria, J.: A method to solve the traveling salesman problem using ant colony optimization variants with ant set partitioning. In: Castillo, O., Melin, P., Kacprzyk, J. (eds.) Recent Advances on Hybrid Intelligent Systems. SCI, vol. 451, pp. 237–246. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  9. Wu, B., Shi, Z.Z.: An Ant Colony Algorithm Based Partition Algorithm for TSP. Chinese journal of computers 24(12), 1328–1333 (2001). (in Chinese)

    MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Management, Shanghai University of Engineering Science, Shanghai, 201620, China

    Sheng Liu & Xiaoming You

Authors
  1. Sheng Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiaoming You
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sheng Liu .

Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Xi'an Jiaotong-Liverpool University, Suzhou, China

    Yuhui Shi

  3. Universidade de Pernambuco, Recife, Brazil

    Fernando Buarque

  4. Instituto Politécnico Nacional, Mexico, Mexico

    Alexander Gelbukh

  5. Indian Statistical Institute, Kolkata, India

    Swagatam Das

  6. University of Pretoria, Pretoria, South Africa

    Andries Engelbrecht

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Liu, S., You, X. (2015). Multi-Colony Ant Algorithm Using a Sociometry-Based Network and Its Application. In: Tan, Y., Shi, Y., Buarque, F., Gelbukh, A., Das, S., Engelbrecht, A. (eds) Advances in Swarm and Computational Intelligence. ICSI 2015. Lecture Notes in Computer Science(), vol 9140. Springer, Cham. https://doi.org/10.1007/978-3-319-20466-6_22

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-20466-6_22

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-20465-9

  • Online ISBN: 978-3-319-20466-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation