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Solving Graph Coloring Problems Using Learning Automata

  • Conference paper
Evolutionary Computation in Combinatorial Optimization (EvoCOP 2008)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4972))

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Abstract

The graph coloring problem (GCP) is a widely studied combinatorial optimization problem with numerous applications, including time tabling, frequency assignment, and register allocation. The growing need for more efficient algorithms has led to the development of several GCP solvers. In this paper, we introduce the first GCP solver that is based on Learning Automata (LA). We enhance traditional Random Walk with LA-based learning capability, encoding the GCP as a Boolean satisfiability problem (SAT). Extensive experiments demonstrate that the LA significantly improve the performance of RW, thus laying the foundation for novel LA-based solutions to the GCP.

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Jano van Hemert Carlos Cotta

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Bouhmala, N., Granmo, OC. (2008). Solving Graph Coloring Problems Using Learning Automata. In: van Hemert, J., Cotta, C. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2008. Lecture Notes in Computer Science, vol 4972. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78604-7_24

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  • DOI: https://doi.org/10.1007/978-3-540-78604-7_24

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-78603-0

  • Online ISBN: 978-3-540-78604-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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