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A Parallel Island Model for Estimation of Distribution Algorithms

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Towards a New Evolutionary Computation

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 192))

Summary

In this work we address the parallelization of the kind of Evolutionary Algorithms (EAs) known as Estimation of Distribution Algorithms (EDAs). After an initial discussion on the types of potentially parallel schemes for EDAs, we proceed to design a distributed island version (dEDA), aimed at improving the numerical efficiency of the sequential algorithm in terms of the number of evaluations. After evaluating such a dEDA on several well-known discrete and continuous test problems, we conclude that our model clearly outperforms existing centralized approaches from a numerical point of view, as well as speeding up the search considerably, thanks to its suitability for physical parallelism.

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Author information

Authors and Affiliations

  1. Department of Computing, Camagüey University, Circunvalación Norte km. 5 1/2, Camagüey, Cuba

    Julio Madera

  2. Department of Languages and Computer Science, Málaga University, Campus de Teatinos (3-2-12), 29071, Málaga, Spain

    Enrique Alba

  3. Institute of Cybernetics, Mathematics and Physics, Calle 15 No. 551 e/C y D, 10400, La Habana, Cuba

    Alberto Ochoa

Authors
  1. Julio Madera
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  2. Enrique Alba
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  3. Alberto Ochoa
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Artificial Intelligence, University of the Basque Country, Apartado de correos 649, 20080, Donostia-San Sebastian, Spain

    Jose A. Lozano , Pedro Larrañaga  & Iñaki Inza ,  & 

  2. Intelligent Systems Group, Department of Architecture and Computer Technology, University of the Basque Country, 20080, Donostia-San Sebastián, Spain

    Endika Bengoetxea

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© 2006 Springer-Verlag Berlin Heidelberg

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Madera, J., Alba, E., Ochoa, A. (2006). A Parallel Island Model for Estimation of Distribution Algorithms. In: Lozano, J.A., Larrañaga, P., Inza, I., Bengoetxea, E. (eds) Towards a New Evolutionary Computation. Studies in Fuzziness and Soft Computing, vol 192. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32494-1_7

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  • DOI: https://doi.org/10.1007/3-540-32494-1_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-29006-3

  • Online ISBN: 978-3-540-32494-2

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