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Study on the Time Development of Complex Network for Metaheuristic

  • Roman SenkerikEmail author
  • Adam Viktorin
  • Michal Pluhacek
  • Jakub Janostik
  • Zuzana Kominkova Oplatkova
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 464)

Abstract

This work deals with the hybridization of the complex networks framework and evolutionary algorithms. The population is visualized as an evolving complex network, which exhibits non-trivial features. This paper investigates briefly the time development of complex network within the run of selected metaheuristic algorithm, which is Differential Evolution (DE). This paper also briefly discuss possible utilization of the complex network attributes such as adjacency graph, centralities, clustering coefficient and others. Experiments were performed for one selected DE strategy and one simple test function.

Keywords

Complex networks Graphs Analysis Differential evolution 

Notes

Acknowledgements

This work was supported by Grant Agency of the Czech Republic—GACR P103/15/06700S, further by This work was supported by the Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme project No. LO1303 (MSMT-7778/2014) and also by the European Regional Development Fund under the project CEBIA-Tech No. CZ.1.05/2.1.00/03.0089, and by Internal Grant Agency of Tomas Bata University under the project No. IGA/CebiaTech/2016/007.

References

  1. 1.
    Zelinka, I., Davendra, D., Lampinen, J., Senkerik, R., Pluhacek, M.: Evolutionary algorithms dynamics and its hidden complex network structures. In: 2014 IEEE Congress on Evolutionary Computation (CEC), pp. 3246–3251 (2014)Google Scholar
  2. 2.
    Davendra, D., Zelinka, I., Metlicka, M., Senkerik, R., Pluhacek, M.: Complex network analysis of differential evolution algorithm applied to flowshop with no-wait problem. In: 2014 IEEE Symposium on Differential Evolution (SDE), pp. 1–8 (2014)Google Scholar
  3. 3.
    Davendra, D., Zelinka, I., Senkerik, R., Pluhacek, M.: Complex network analysis of evolutionary algorithms applied to combinatorial optimisation problem. In: Kömer, P., Abraham, A., Snášel, V. (eds.) Proceedings of the Fifth International Conference on Innovations in Bio-Inspired Computing and Applications IBICA 2014. Springer International Publishing, pp. 141–150 (2014)Google Scholar
  4. 4.
    Skanderova, L., Fabian, T.: Differential evolution dynamics analysis by complex networks. Soft Comput. 1–15 (2015)Google Scholar
  5. 5.
    Metlicka, M., Davendra, D.: Ensemble centralities based adaptive Artificial Bee algorithm. In: 2015 IEEE Congress on Evolutionary Computation (CEC), pp. 3370–3376 (2015)Google Scholar
  6. 6.
    Gajdos, P., Kromer, P., Zelinka, I.: Network visualization of population dynamics in the differential evolution. In: 2015 IEEE Symposium Series on Computational Intelligence, pp. 1522–1528 (2015)Google Scholar
  7. 7.
    Price, K.V.: An introduction to differential evolution. In: Corne, D., Dorigo, M., Glover, F. (eds.) New Ideas in Optimization. McGraw-Hill Ltd., pp. 79–108 (1999)Google Scholar
  8. 8.
    Qin, A.K., Huang, V.L., Suganthan, P.N.: Differential evolution algorithm with strategy adaptation for global numerical optimization. IEEE Trans. Comput. Evol. 13(2), 398–417 (2009)CrossRefGoogle Scholar
  9. 9.
    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(2), 1679–1696 (2011)CrossRefGoogle Scholar
  10. 10.
    Price, K.V., Storn, R.M., Lampinen, J.A.: Differential Evolution—A Practical Approach to Global Optimization. Natural Computing Series. Springer Berlin Heidelberg (2005)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Roman Senkerik
    • 1
    Email author
  • Adam Viktorin
    • 1
  • Michal Pluhacek
    • 1
  • Jakub Janostik
    • 1
  • Zuzana Kominkova Oplatkova
    • 1
  1. 1.Faculty of Applied InformaticsTomas Bata University in ZlinZlínCzech Republic

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