Skip to main content
SpringerLink
Log in
Book cover

International Conference on Artificial Intelligence and Soft Computing

ICAISC 2017: Artificial Intelligence and Soft Computing pp 408–417Cite as

Controlling Population Size in Differential Evolution by Diversity Mechanism

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10245))

Abstract

A new mechanism for resizing population in differential evolution algorithm based on diversity of population has been proposed and compared with linear reduction of population size published in 2014. Seven modifications of differential evolution algorithm were chosen for this comparison. Experiments are done on CEC2014 benchmark set. The new diversity-based resizing mechanism frequently improves results of tested variants of differential evolution algorithm more than linear reduction of population size, especially in larger dimensions.

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 EPUB and 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

Learn about institutional subscriptions

References

  1. Brest, J., Greiner, S., Boškovič, B., Mernik, M., Žumer, V.: Self-adapting control parameters in differential evolution: A comparative study on numerical benchmark problems. IEEE Trans. Evol. Comput. 10, 646–657 (2006)

    Article  Google Scholar 

  2. Bujok, P., Tvrdík, J., Poláková, R.: Differential evolution with rotation-invariant mutation and competing-strategies adaptation. IEEE Congr. Evol. Comput. 2014, 2253–2258 (2014)

    Google Scholar 

  3. Das, S., Suganthan, P.N.: Differential evolution: A survey of the state-of-the-art. IEEE Trans. Evol. Comput. 15, 27–54 (2011)

    Google Scholar 

  4. Kaelo, P., Ali, M.M.: A numerical study of some modified differential evolution algorithms. Eur. J. Oper. Res. 169, 1176–1184 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  5. Lampinen, J., Zelinka, I.: On stagnation of differential evolution algorithm. In: 6th International Conference on Soft Computing, MENDEL 2000, pp. 76–83 (2000)

    Google Scholar 

  6. Liang, J.J., Qu, B., Suganthan, P.N.: Problem definitions and evaluation criteria for the CEC 2014 special session and competition on single objective real-parameter numerical optimization (2013). http://www.ntu.edu.sg/home/epnsugan/

  7. Liang, J.J., Qu, B., Suganthan, P.N.: Ranking results of CEC14 special session and competition on real-parameter single objective optimization (2014). http://www3.ntu.edu.sg/home/epnsugan/

  8. Liang, J.J., Qu, B., Suganthan, P.N., Hernández-Díaz, A.G.: Problem definitions and evaluation criteria for the CEC 2013 special session on real-parameter optimization (2013). http://www.ntu.edu.sg/home/epnsugan/

  9. Loshchilov, I., Stuetzle, T., Liao, T.: Ranking results of CEC 2013 special session and competition on real-parameter single objective optimization (2013). http://www3.ntu.edu.sg/home/epnsugan/

  10. Mallipeddi, R., Suganthan, P.N., Pan, Q.K., Tasgetiren, M.F.: Differential evolution algorithm with ensemble of parameters and mutation strategies. Appl. Soft Comput. 11, 1679–1696 (2011)

    Article  Google Scholar 

  11. Poláková, R., Tvrdík, J., Bujok, P.: Controlled restart in differential evolution applied to CEC 2014 benchmark functions. IEEE Congr. Evol. Comput. 2014, 2230–2236 (2014)

    Google Scholar 

  12. Poláková, R., Tvrdík, J., Bujok, P.: Population-size adaptation through diversity-control mechanism for differential evolution. In: 22nd International Conference on Soft Computing MENDEL 2016, Brno, pp. 49–56 (2016)

    Google Scholar 

  13. Storn, R., Price, K.: Differential evolution - a simple and efficient heuristic for global optimization over continuous spaces. J. Glob. Optim. 11, 341–359 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  14. Tanabe, R., Fukunaga, A.: Success-history based parameter adaptation for differential evolution. IEEE Congr. Evol. Comput. 2013, 71–78 (2013)

    Google Scholar 

  15. Tanabe, R., Fukunaga, A.: Improving the search performance of SHADE using linear population size reduction. IEEE Congr. Evol. Comput. 2014, 1658–1665 (2014)

    Google Scholar 

  16. Tang, L., Dong, Y., Liu, J.: Differential evolution with an individual-dependent mechanism. IEEE Trans. Evol. Comput. 19, 560–574 (2015)

    Article  Google Scholar 

  17. Tvrdík, J.: Competitive differential evolution. In: Matoušek, R., Ošmera, P. (eds.) MENDEL 2006, 12th International Conference on Soft Computing, pp. 7–12 (2006)

    Google Scholar 

  18. Tvrdík, J., Poláková, R.: Competitive differential evolution applied to CEC 2013 problems. IEEE Congr. Evol. Comput. 2013, 1651–1657 (2013)

    Google Scholar 

  19. Wang, Y., Cai, Z., Zhang, Q.: Differential evolution with composite trial vector generation strategies and control parameters. IEEE Trans. Evol. Comput. 15, 55–66 (2011)

    Article  Google Scholar 

  20. Zhang, J., Sanderson, A.C.: JADE: Adaptive differential evolution with optional external archive. IEEE Trans. Evol. Comput. 13, 945–958 (2009)

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported by the project LQ1602 IT4Innovations excellence in science.

Author information

Authors and Affiliations

  1. Centre of Excellence IT4 Innovations, Institute for Research and Applications of Fuzzy Modeling, Division of University of Ostrava, 30. dubna Street 22, 701 03, Ostrava, Czech Republic

    Radka Poláková

Authors
  1. Radka Poláková
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Radka Poláková .

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  3. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  4. AGH University of Science and Technology, Kraków, Poland

    Ryszard Tadeusiewicz

  5. University of California, Berkeley, California, USA

    Lotfi A. Zadeh

  6. University of Louisville, Louisville, Kentucky, USA

    Jacek M. Zurada

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Poláková, R. (2017). Controlling Population Size in Differential Evolution by Diversity Mechanism. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2017. Lecture Notes in Computer Science(), vol 10245. Springer, Cham. https://doi.org/10.1007/978-3-319-59063-9_36

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-59063-9_36

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59062-2

  • Online ISBN: 978-3-319-59063-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation