On the Prolonged Exploration of Distance Based Parameter Adaptation in SHADE

  • Adam ViktorinEmail author
  • Roman Senkerik
  • Michal Pluhacek
  • Tomas Kadavy
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10841)


In this paper, a prolonged exploration ability of distance based parameter adaptation is subject to a test via clustering analysis of the population in Success-History based Adaptive Differential Evolution (SHADE). The comparative study is done on the CEC 2015 benchmark set in two dimensional settings – 10D and 30D. It is shown, that the exploration phase of distance based adaptation in SHADE (Db_SHADE) lasts for more generations and therefore avoids the premature convergence into local optima.


Distance based parameter adaptation SHADE Db_SHADE Clustering analysis DBSCAN Exploration Exploitation 


  1. 1.
    Storn, R., Price, K.: Differential Evolution-A Simple and Efficient Adaptive Scheme for Global Optimization over Continuous Spaces, vol. 3. ICSI, Berkeley (1995)zbMATHGoogle Scholar
  2. 2.
    Gämperle, R., Müller, S.D., Koumoutsakos, P.: A parameter study for differential evolution. Adv. Intell. Syst. Fuzzy Syst. Evol. Comput. 10, 293–298 (2002)Google Scholar
  3. 3.
    Liu, J., Lampinen, J.: On setting the control parameter of the differential evolution method. In: Proceedings of the 8th International Conference on Soft Computing (MENDEL 2002), pp. 11–18 (2002)Google Scholar
  4. 4.
    Neri, F., Tirronen, V.: Recent advances in differential evolution: a survey and experimental analysis. Artif. Intell. Rev. 33(1–2), 61–106 (2010)CrossRefGoogle Scholar
  5. 5.
    Das, S., Suganthan, P.N.: Differential evolution: a survey of the state-of-the-art. IEEE Trans. Evol. Comput. 15(1), 4–31 (2011)CrossRefGoogle Scholar
  6. 6.
    Das, S., Mullick, S.S., Suganthan, P.N.: Recent advances in differential evolution-an updated survey. Swarm Evol. Comput. 27, 1–30 (2016)CrossRefGoogle Scholar
  7. 7.
    Tanabe, R., Fukunaga, A.: Success-history based parameter adaptation for differential evolution. In: 2013 IEEE Congress on Evolutionary Computation (CEC), pp. 71–78. IEEE, June 2013Google Scholar
  8. 8.
    Tanabe, R., Fukunaga, A.S.:. Improving the search performance of SHADE using linear population size reduction. In: 2014 IEEE Congress on Evolutionary Computation (CEC), pp. 1658–1665. IEEE, July 2014Google Scholar
  9. 9.
    Guo, S.M., Tsai, J.S.H., Yang, C.C., Hsu, P.H.: A self-optimization approach for L-SHADE incorporated with eigenvector-based crossover and successful-parent-selecting framework on CEC 2015 benchmark set. In: 2015 IEEE Congress on Evolutionary Computation (CEC), pp. 1003–1010. IEEE, May 2015Google Scholar
  10. 10.
    Awad, N.H., Ali, M.Z., Suganthan, P.N., Reynolds, R.G.: An ensemble sinusoidal parameter adaptation incorporated with L-SHADE for solving CEC2014 benchmark problems. In: 2016 IEEE Congress on Evolutionary Computation (CEC), pp. 2958–2965. IEEE, July 2016Google Scholar
  11. 11.
    Brest, J., Maučec, M.S., Bošković, B.: Single objective real-parameter optimization: algorithm jSO. In: 2017 IEEE Congress on Evolutionary Computation (CEC), pp. 1311–1318. IEEE, June 2017Google Scholar
  12. 12.
    Viktorin, A., Senkerik, R., Pluhacek, M., Kadavy, T., Zamuda, A.: Distance based parameter adaptation for differential evolution. In: IEEE Symposium Series on Computational Intelligence (SSCI), pp. 2612–2618. IEEE (2017, in press)Google Scholar
  13. 13.
    Zhang, J., Sanderson, A.C.: JADE: adaptive differential evolution with optional external archive. IEEE Trans. Evol. Comput. 13(5), 945–958 (2009)CrossRefGoogle Scholar
  14. 14.
    Ester, M., Kriegel, H.P., Sander, J., Xu, X.: A density-based algorithm for discovering clusters in large spatial databases with noise. In: KDD, vol. 96, no. 34, pp. 226–231, August 1996Google Scholar
  15. 15.
    Deza, M.M., Deza, E.: Encyclopedia of distances. In: Deza, M.M., Deza, E. (eds.) Encyclopedia of Distances, pp. 1–583. Springer, Berlin (2009). Scholar

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© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Faculty of Applied InformaticsTomas Bata University in ZlinZlinCzech Republic

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