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Position-Guided Tabu Search Algorithm for the Graph Coloring Problem

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Learning and Intelligent Optimization (LION 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5851))

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Abstract

A very undesirable behavior of any heuristic algorithm is to be stuck in some specific parts of the search space, in particular in the basins of attraction of the local optima. While there are many well-studied methods to help the search process escape a basin of attraction, it seems more difficult to prevent it from looping between a limited number of basins of attraction. We introduce a Position Guided Tabu Search (PGTS) heuristic that, besides avoiding local optima, also avoids re-visiting candidate solutions in previously visited regions. A learning process, based on a metric of the search space, guides the Tabu Search toward yet unexplored regions. The results of PGTS for the graph coloring problem are competitive. It significantly improves the results of the basic Tabu Search for almost all tested difficult instances from the DIMACS Challenge Benchmark and it matches most of the best results from the literature.

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Author information

Authors and Affiliations

  1. LERIA, Université d’Angers, Angers, France

    Daniel Cosmin Porumbel & Jin-Kao Hao

  2. LINA, Polytech’Nantes, Nantes, France

    Daniel Cosmin Porumbel & Pascale Kuntz

Authors
  1. Daniel Cosmin Porumbel
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  2. Jin-Kao Hao
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  3. Pascale Kuntz
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Editor information

Editors and Affiliations

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

    Thomas Stützle

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© 2009 Springer-Verlag Berlin Heidelberg

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Porumbel, D.C., Hao, JK., Kuntz, P. (2009). Position-Guided Tabu Search Algorithm for the Graph Coloring Problem. In: Stützle, T. (eds) Learning and Intelligent Optimization. LION 2009. Lecture Notes in Computer Science, vol 5851. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11169-3_11

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  • DOI: https://doi.org/10.1007/978-3-642-11169-3_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-11168-6

  • Online ISBN: 978-3-642-11169-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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