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Parallel Migration Model Employing Various Adaptive Variants of Differential Evolution

  • Conference paper
Swarm and Evolutionary Computation (EC 2012, SIDE 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7269))

Abstract

The influence of migration on the performance of differential evolution algorithm is studied. Six adaptive variants of differential evolution are applied to a parallel migration model with a star topology. The parallel algorithm with several different settings of parameters controlling the migration was experimentally compared with the adaptive serial algorithms in six benchmark problems of dimension D = 30. The parallel algorithm was more efficient than the best serial adaptive DE variant in a half of the problems.

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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 Transactions on Evolutionary Computation 10, 646–657 (2006)

    Article  Google Scholar 

  2. Bujok, P.: Parallel models of adaptive differential evolution based on migration process. In: Aplimat, 10th International Conference on Applied Mathematics, Bratislava, pp. 357–364 (2011)

    Google Scholar 

  3. Cantu-Paz, E.: A survey of parallel genetic algorithms (1997), http://neo.lcc.uma.es/cEA-web/documents/cant98.pdf

  4. Das, S., Suganthan, P.N.: Differential evolution: A survey of the state-of-the-art. IEEE Transactions on Evolutionary Computation 15, 27–54 (2011)

    Google Scholar 

  5. Iacca, G., Mallipeddi, R., Mininno, E., Neri, F., Suganthan, P.N.: Global supervision for compact differential evolution. In: Proceeding IEEE Symposium on Differential Evolution, Paris, France, pp. 25–32 (2011)

    Google Scholar 

  6. Kaelo, P., Ali, M.M.: A numerical study of some modified differential evolution algorithms. European J. Operational Research 169, 1176–1184 (2006)

    Article  MathSciNet  MATH  Google Scholar 

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

    Article  Google Scholar 

  8. Nedjah, N., Alba, E., de Macedo Mourelle, L.: Parallel Evolutionary Computations. SCI. Springer-Verlag New York Inc., Secaucus (2006)

    Book  MATH  Google Scholar 

  9. Neri, F., Tirronen, V.: Recent advances in differential evolution: a review and experimental analysis. Artificial Intelligence Review 33, 61–106 (2010)

    Article  Google Scholar 

  10. Price, K.V., Storn, R., Lampinen, J.: Differential Evolution: A Practical Approach to Global Optimization. Springer, Heidelberg (2005)

    MATH  Google Scholar 

  11. Qin, A.K., Huang, V.L., Suganthan, P.N.: Differential evolution algorithm with strategy adaptation for global numerical optimization. IEEE Transactions on Evolutionary Computation 13(2), 398–417 (2009)

    Article  Google Scholar 

  12. Ruciński, M., Izzo, D., Biscani, F.: On the impact of the migration topology on the island model. Parallel Comput. 36, 555–571 (2010)

    Article  MATH  Google Scholar 

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

    Article  MathSciNet  MATH  Google Scholar 

  14. Tasoulis, D.K., Pavlidis, N., Plagianakos, V.P., Vrahatis, M.N.: Parallel differential evolution. In: IEEE Congress on Evolutionary Computation (CEC), pp. 2023–2029 (2004)

    Google Scholar 

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

    Google Scholar 

  16. Tvrdík, J.: Self-adaptive variants of differential evolution with exponential crossover. Series Mathematics-Informatics, vol. 47, pp. 151–168. Analele of West University Timisoara (2009), http://www1.osu.cz/~tvrdik/ (reprint available [ONLINE])

  17. Wang, Y., Cai, Z., Zhang, Q.: Differential evolution with composite trial vector generation strategies and control parameters. IEEE Transactions on Evolutionary Computation 15, 55–66 (2011)

    Article  Google Scholar 

  18. Weber, M., Tirronen, V., Neri, F.: Scale factor inheritance mechanism in distributed differential evolution. Soft Computing. A Fusion of Foundations Methodologies and Applications 14(11), 1187–1207 (2010)

    Google Scholar 

  19. Zaharie, D.: Influence of crossover on the behavior of differential evolution algorithms. Applied Soft Computing 9, 1126–1138 (2009)

    Article  Google Scholar 

  20. Zhang, J., Sanderson, A.C.: JADE: Adaptive Differential Evolution With Optional External Archive. IEEE Transactions on Evolutionary Computation 13 (2009)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Ostrava, Czech Republic

    Petr Bujok

  2. Institute for Research and Applications of Fuzzy Modeling, Centre of Excellence IT4Innovations, Division of University of Ostrava, 30. dubna 22, 70103, Ostrava, Czech Republic

    Josef Tvrdík

Authors
  1. Petr Bujok
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  2. Josef Tvrdík
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Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Armii Krajowej 36, 42-200, Częstochowa, Poland

    Leszek Rutkowski , Marcin Korytkowski  & Rafał Scherer ,  & 

  2. AGH University of Science and Technology, Mickiewicza 30, 30-059, Kraków, Poland

    Ryszard Tadeusiewicz

  3. Department of Electrical Engineering and Computer Sciences, Computer Science Division, University of California Berkeley, 94720-1776, Berkeley, CA, USA

    Lotfi A. Zadeh

  4. Computational Intelligence Laboratory, Electrical and Computer Engineering, University of Louisville, 405 Lutz Hallz, 40292, Louisville, KY, USA

    Jacek M. Zurada

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© 2012 Springer-Verlag Berlin Heidelberg

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Bujok, P., Tvrdík, J. (2012). Parallel Migration Model Employing Various Adaptive Variants of Differential Evolution. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Swarm and Evolutionary Computation. EC SIDE 2012 2012. Lecture Notes in Computer Science, vol 7269. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29353-5_5

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  • DOI: https://doi.org/10.1007/978-3-642-29353-5_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29352-8

  • Online ISBN: 978-3-642-29353-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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