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International Workshop on Ant Colony Optimization and Swarm Intelligence

ANTS 2006: Ant Colony Optimization and Swarm Intelligence pp 492–499Cite as

Some Experiments with Ant Colony Algorithms for the Exam Timetabling Problem

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4150))

Abstract

The exam timetabling problem faces the problem of scheduling exams within a limited number of available periods. The main objective is to balance out student’s workload by distributing the exams evenly within the planning horizon. Ant colony approaches have been proven to be a powerful solution approach for various combinatorial optimization problems. In this paper a Max-Min and a ANTCOL approach will be presented. Its performance is compared with other approaches presented in the literature and with modified graph coloring algorithms.

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Author information

Authors and Affiliations

  1. Logistics Laboratory (LlAb), Faculty of Engineering, Aschaffenburg University of Applied Science, Aschaffenburg, Germany

    Michael Eley

Authors
  1. Michael Eley
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Editor information

Editors and Affiliations

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

    Marco Dorigo

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

    Luca Maria Gambardella

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

    Mauro Birattari

  4. Swarm-Intelligent Systems Group, École Polytechnique Fédérale de Lausanne, 1015, Lausanne, Switzerland

    Alcherio Martinoli

  5. Department of Computing and Electronic Systems, University of Essex, Wivenhoe Park, CO4 3SQ, Colchester, UK

    Riccardo Poli

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

    Thomas Stützle

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© 2006 Springer-Verlag Berlin Heidelberg

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Eley, M. (2006). Some Experiments with Ant Colony Algorithms for the Exam Timetabling Problem. In: Dorigo, M., Gambardella, L.M., Birattari, M., Martinoli, A., Poli, R., Stützle, T. (eds) Ant Colony Optimization and Swarm Intelligence. ANTS 2006. Lecture Notes in Computer Science, vol 4150. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11839088_50

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  • DOI: https://doi.org/10.1007/11839088_50

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-38482-3

  • Online ISBN: 978-3-540-38483-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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