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Automatic Configuration of Multi-Objective ACO Algorithms

  • Conference paper
Swarm Intelligence (ANTS 2010)

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

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Abstract

In the last few years a significant number of ant colony optimization (ACO) algorithms have been proposed for tackling multi-objective optimization problems. In this paper, we propose a software framework that allows to instantiate the most prominent multi-objective ACO (MOACO) algorithms. More importantly, the flexibility of this MOACO framework allows the application of automatic algorithm configuration techniques. The experimental results presented in this paper show that such an automatic configuration of MOACO algorithms is highly desirable, given that our automatically configured algorithms clearly outperform the best performing MOACO algorithms that have been proposed in the literature. As far as we are aware, this paper is also the first to apply automatic algorithm configuration techniques to multi-objective stochastic local search algorithms.

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Author information

Authors and Affiliations

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

    Manuel López-Ibáñez & Thomas Stützle

Authors
  1. Manuel López-Ibáñez
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  2. Thomas Stützle
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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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López-Ibáñez, M., Stützle, T. (2010). Automatic Configuration of Multi-Objective ACO Algorithms. 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_9

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  • DOI: https://doi.org/10.1007/978-3-642-15461-4_9

  • 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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