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EDA-PSO: A Hybrid Paradigm Combining Estimation of Distribution Algorithms and Particle Swarm Optimization

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Swarm Intelligence (ANTS 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6234))

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Abstract

Estimation of Distribution Algorithms (EDAs) is an evolutionary computation optimization paradigm that relies the evolution of each generation on calculating a probabilistic graphical model able to reflect dependencies among variables out of the selected individuals of the population. This showed to be able to improve results with GAs for complex problems.

This paper presents a new hybrid approach combining EDAs and particle swarm optimization, with the aim to take advantage of EDAs capability to learn from the dependencies between variables while profiting particle swarm’s optimization ability to keep a sense of ”direction” towards the most promising areas of the search space. Experimental results show the validity of this approach with widely known combinatorial optimization problems.

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Author information

Authors and Affiliations

  1. Intelligent Systems Group, University of the Basque Country, San Sebastian, Spain

    Endika Bengoetxea

  2. Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, Madrid, Spain

    Pedro Larrañaga

Authors
  1. Endika Bengoetxea
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  2. Pedro Larrañaga
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Editor information

Editors and Affiliations

  1. IRIDIA, CoDE, Université Libre de Bruxelles, Brussels, Belgium

    Marco Dorigo

  2. IRIDIA, CoDE, Université Libre de Bruxelles, Av. F. Roosevelt 50, CP 194/6, 1050, Brussels, Belgium

    Mauro Birattari

  3. ’Dalla Molle’ Institute for Artificial Intelligence (IDSIA), Galleria 2, 6928, Manno-Lugano, Switzerland

    Gianni A. Di Caro

  4. Complex Systems Institute, Paris-Ile-de-France, CREA, Ecole Polytechnique & CNRS, 57-59, rue Lhomond, 75005, Paris, France

    René Doursat

  5. Department of Computer Science, University of Pretoria, 0002, P.O. Box, Pretoria, South Africa

    Andries P. Engelbrecht

  6. EPFL, Laboratory of Intelligent Systems, Lausanne, Switzerland

    Dario Floreano

  7. Istituto Dalle Molle di Studi sull’Intelligenza Artificiale (IDSIA), Lugano, Switzerland

    Luca Maria Gambardella

  8. Department of Automatic Control and Systems Engineering, The University of Sheffield, Mappin Street, S1 3JD, Sheffield, UK

    Roderich Groß

  9. KOVAN Research Lab., Department of Computer Engineering, Middle East Technical University, Inonu Bulvari, 06531, Ankara, Turkey

    Erol Şahin

  10. Department of Bioengineering, Binghamton University, State University of New York, 13902-6000, Binghamton NY, USA

    Hiroki Sayama

  11. IRIDIA, CoDE, Université Libre de Bruxelles, Avenue F. Roosevelt 50, CP 194/6, 1050, Brussels, Belgium

    Thomas Stützle

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Bengoetxea, E., Larrañaga, P. (2010). EDA-PSO: A Hybrid Paradigm Combining Estimation of Distribution Algorithms and Particle Swarm Optimization. In: Dorigo, M., et al. Swarm Intelligence. ANTS 2010. Lecture Notes in Computer Science, vol 6234. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15461-4_39

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  • DOI: https://doi.org/10.1007/978-3-642-15461-4_39

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15460-7

  • Online ISBN: 978-3-642-15461-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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