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Gravitational Swarm Approach for Graph Coloring

  • Israel Rebollo Ruiz
  • Manuel Graña Romay
Part of the Studies in Computational Intelligence book series (SCI, volume 387)

Abstract

We introduce a new nature inspired algorithm to solve the Graph Coloring Problem (GCP): the Gravitational Swarm. The Swarm is composed of agents that act individually, but that can solve complex computational problems when viewed as a whole. We formulate the agent’s behavior to solve the GCP. Agents move as particles in the gravitational field defined by some target objects corresponding to graph node colors. Knowledge of the graph to be colored is encoded in the agents as friend-or-foe information. We discuss the convergence of the algorithm and test it over well-known benchmarking graphs, achieving good results in a reasonable time.

Keywords

Particle Swarm Optimization Chromatic Number Swarm Intelligence Graph Node Iterate Local Search 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Israel Rebollo Ruiz
    • 1
  • Manuel Graña Romay
    • 2
  1. 1.Informática 68 Investigación y Desarrollo S.L., Computational Intelligence GroupUniversity of the Basque CountryBasque Country
  2. 2.Computational Intelligence GroupUniversity of the Basque CountryBasque Country

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