Skip to main content
SpringerLink
Log in

The Analysis Based on the Two Main Applications of Artificial Bee Colony Algorithm

  • Conference paper
  • First Online:
LISS 2012

  • 169 Accesses

Abstract

Artificial bee colony (ABC) algorithm is a relatively new swarm intelligence technique inspired by the intelligent foraging behavior of honey bees. It has shown better performance in many fields including constrained problems and clustering problems, than that of Evolutionary algorithms (EA), Particle Swarm Optimization (PSO) algorithm and Ant Colony Optimization (ACO) algorithm. This paper presents a research on the mechanism of ABC algorithm, analyses the features and disadvantages of two main applications, and provides a method to solve the question of setting parameters automatic.

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 259.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
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

References

  1. Beni G, Wang J (1989) Swarm intelligence in cellular robotic systems. In: NATO advanced workshop on robots and biological systems, Tuscany, 1989, pp 26–30

    Google Scholar 

  2. Kennedy J, Eberhart R (1995) Particle swarm optimization. In: IEEE international conference on neural networks, Washington, DC, 1995, pp 1942–1948

    Google Scholar 

  3. Dorigo M, Stutzle T (2004) Ant colony optimization. MIT Press, Cambridge

    Book  Google Scholar 

  4. Karaboga D, Basturk B (2007) A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm. J Glob Optim 39:459–471

    Article  Google Scholar 

  5. Karaboga D, Basturk B (2007) Artificial Bee Colony (ABC) Optimization Algorithm for Solving Constrained Optimization Problems [C]. Proc. of Advances in Soft Computing: Foundations of Fuzzy Logic and Soft Computing. Berlin, Germany: Springer-Verlag, 789–798

    Google Scholar 

  6. Szetoa WY, Yongzhong Wu (2011) An artificial bee colony algorithm for the capacitated vehicle routing problem. Eur J Op Res 215:126–135

    Article  Google Scholar 

  7. Sundar S, Singh A (2010) A swarm intelligence approach to the quadratic minimum spanning tree problem. Inform Sci 180:3182–3191

    Article  Google Scholar 

  8. Goldberg DE, Deb K (1991) A comparison of selection schemes used in genetic algorithms. In: Rawlins GJE (ed) Foundations of genetic algorithms. Morgan Kaufmann Publishers, San Mateo, pp 69–93

    Google Scholar 

  9. Karaboga D (2005) An Idea Based on Honey Bee Swarm for Numerical Optimization [R]. [S. l.]: Erciyes University, Technical Report: TR06

    Google Scholar 

  10. Bu Denghui (2011) Artificial bee colony algorithm based on dynamic wholly updating and tentative mechanism. Appl Res Comput 28:2508–2511

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. College of Information Engineering, Capital Normal University, 100048, Beijing Haidian District West Ring North Road No. 56, Beijing, China

    Yanfei Wang

  2. College of Information Engineering, Capital Normal University, 100048, Beijing, China

    Jun Xie & Zhengguang Xian

  3. College Department of Computer Science and Technology, Tsinghua National Laboratory of Information Science and Technology, Tsinghua University, Beijing, 100084, China

    Jun Xie

Authors
  1. Yanfei Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jun Xie
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zhengguang Xian
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yanfei Wang .

Editor information

Editors and Affiliations

  1. Beijing Jiaotong University, Beijing, 100044, China, People's Republic

    Zhenji Zhang

  2. , Department of information Management, Beijing Jiaotong University, 3 Shangyuancun, Xizhimenwai, Beijing, 100044, China, People's Republic

    Runtong Zhang

  3. , School of Economics and Management, Beijing Jiaotong University, Haidian District, Beijing, 100044, China, People's Republic

    Juliang Zhang

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Wang, Y., Xie, J., Xian, Z. (2013). The Analysis Based on the Two Main Applications of Artificial Bee Colony Algorithm. In: Zhang, Z., Zhang, R., Zhang, J. (eds) LISS 2012. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32054-5_198

Download citation

Publish with us

Policies and ethics

Search

Navigation