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Ant Colony Extended: Search in Solution Spaces with a Countably Infinite Number of Solutions

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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

Ant Colony Extended (ACE) is a new framework that allows to apply the ant colony paradigm [1] to solve combinatorial optimization problems, in which the values of each variable are taken from a finite set, and the set of possible solutions is countably infinite.

Previously, we applied ACE to autonomous ship manoeuvre planning [2], where the objective was to minimize the time of a manoeuvre. In this problem, as in the TSP and others, the value of the cost function increases monotonically as new elements are added to the solution sequence. We want to check the algorithm for problems that do not exhibit this feature. For this purpose we select a set of multi-modal functions to minimize with ACE: Griewank’s function (F2), Shekel’s foxholes (F3), Michalewicz’ function (F4) and Langerman’s function (F5). All functions are taken from [4].

These functions have many local minima, where algorithms may get stuck.We select the Simple Genetic Algorithm (SGA), and Differential Evolution (DE) to perform a comparison of local minima avoidance.

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References

  1. Dorigo, M., Stützle, T.: Ant colony optimization. The MIT Press, Cambridge (2004)

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  2. Escario, J.B., Jimenez, J.F., Giron-Sierra, J.M.: Autonomous ship manoeuvring planning based on the ant colony optimization algorithm. In: Proceedings of 8th Conference on Manoeuvring and Control of Marine Craft, MCMC 2009 (2009)

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  3. Gordon, D.: Ants at work: how an insect society is organized. Free Press, New York (1999)

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  4. Seront, G., Gambardella, L.: Results of the first international contest on evolutionary optimisation. In: Proceedings of 1st ICEO IEEE International Conference on Evolutionary Computation, pp. 611–615 (1996)

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Author information

Authors and Affiliations

  1. Arquitectura de Computadores y Automatica Dept., Universidad Complutense, Madrid, Spain

    Jose B. Escario, Juan F. Jimenez & Jose M. Giron-Sierra

Authors
  1. Jose B. Escario
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  2. Juan F. Jimenez
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  3. Jose M. Giron-Sierra
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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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© 2010 Springer-Verlag Berlin Heidelberg

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Escario, J.B., Jimenez, J.F., Giron-Sierra, J.M. (2010). Ant Colony Extended: Search in Solution Spaces with a Countably Infinite Number of Solutions. 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_56

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  • DOI: https://doi.org/10.1007/978-3-642-15461-4_56

  • 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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