Skip to main content
SpringerLink
Log in

Parallel Implementation of Synchronous Type Artificial Bee Colony Algorithm for Global Optimization

  • Published:
Journal of Optimization Theory and Applications Aims and scope Submit manuscript

Abstract

Evolutionary algorithms often need huge running times when solving large-scale optimization problems. One of the solutions for this issue is to introduce parallelization into the algorithm. To benefit from this approach for the artificial bee colony optimization algorithm, we present a new synchronous and parallel version of the algorithm. Performances of the proposed version and the original asynchronous algorithm are compared in terms of efficiency and speedup. Algorithms are competed to solve 20 large-scale global optimization problems. Comparative results show that the proposed parallel algorithm is still efficient as asynchronous version while it requires much less time to solve complex and large problems.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Algorithm 1
Algorithm 2
Algorithm 3
Fig. 1

Similar content being viewed by others

References

  1. Schwefel, H.P.: Numerical Optimization of Computer Models. Wiley, Chichester (1981)

    MATH  Google Scholar 

  2. Alba, E., Troya, J.M.: A survey of parallel distributed genetic algorithms. Complexity 4(4), 31–52 (1999)

    Article  MathSciNet  Google Scholar 

  3. Karaboga, D.: An idea based on honey bee swarm for numerical optimization. Tech. Report No. TR06, Erciyes University (2005)

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

    Article  MathSciNet  MATH  Google Scholar 

  5. Luo, R., Pan, S.T., Tsai, P.W., Pan, J.S.: Parallelized artificial bee colony with ripple-communication strategy. In: Fourth International Conference on Genetic and Evolutionary Computing, pp. 350–353 (2010)

    Google Scholar 

  6. Subotic, M., Tuba, M., Stanarevic, N.: Parallelization of the artificial bee colony (ABC) algorithm. In: Proceedings of the 11th WSEAS International Conference on Nural Networks and 11th WSEAS International Conference on Evolutionary Computing and 11th WSEAS International Conference on Fuzzy systems, pp. 191–196 (2010)

    Google Scholar 

  7. Subotic, M., Tuba, M., Stanarevic, N.: Different approaches in parallelization of the artificial bee colony algorithm. Int. J. Math. Models Methods Appl. Sci. 5(4), 755–762 (2011)

    Google Scholar 

  8. Benitez, C.M.V., Lopes, H.S.: Parallel artificial bee colony algorithm approaches for protein structure prediction using the 3DHP-SC model. Intell. Distrib. Comput. IV, 255–264 (2010)

    Article  Google Scholar 

  9. Parpinelli, R.S., Benitez, C.M.V., Lopes, H.S.: Parallel approaches for the artificial bee colony algorithm. In: Panigrahi, B.K., Shi, Y., Lim, M.H., Hiot, L.M., Ong, Y.S. (eds.) Handbook of Swarm Intelligence, Adaptation, Learning, and Optimization, vol. 8, pp. 329–345. Springer, Berlin (2010)

    Google Scholar 

  10. Gabriel, E., Fagg, G.E., Bosilca, G., Angskun, T., Dongarra, J.J., Squyres, J.M., Sahay, V., Kambadur, P., Barrett, B., Lumsdaine, A., Castain, R.H., Daniel, D.J., Graham, R.L., Woodall, T.S.: Open MPI: goals, concept, and design of a next generation MPI implementation. In: 11th European PVM/MPI Users’ Group Meeting Proceedings, pp. 97–104 (2004)

    Google Scholar 

  11. Antoni, G.A., Cabianca, D., Vaccari, M., Benini, M., Casablanca, F.: Linearity of client/server systems. Bull. Eur. Assoc. Theor. Comput. Sci. 57, 201–214 (1995)

    MATH  Google Scholar 

  12. Tang, K., Li, X., Suganthan, P.N., Weise, T.: Benchmark functions for the CEC’2010 special session and competition on large-scale global optimization. Tech. report at http://nical.ustc.edu.cn/cec10ss.php, Nature Inspired Computation and Applications Laboratory, USTC, China (2009)

Download references

Acknowledgements

The numerical calculations reported in this paper are performed at TUBITAK ULAKBIM, High Performance and Grid Computing Center (TR-Grid e-Infrastructure).

This study is a part of the research project under the contract number FBA-11-3520 and the authors would like to thank Erciyes University, Scientific Research Projects Unit.

Author information

Authors and Affiliations

  1. Department of Computer Engineering, Erciyes University, Kayseri, 38039, Turkey

    Alper Basturk

  2. Graduate School of Natural & Applied Sciences, Erciyes University, Kayseri, 38039, Turkey

    Rustu Akay

Authors
  1. Alper Basturk
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rustu Akay
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Alper Basturk.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Basturk, A., Akay, R. Parallel Implementation of Synchronous Type Artificial Bee Colony Algorithm for Global Optimization. J Optim Theory Appl 155, 1095–1104 (2012). https://doi.org/10.1007/s10957-012-0107-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10957-012-0107-5

Keywords

Search

Navigation