Meta-Heuristics for Robust Graph Coloring Problem

  • Authors:

  • Andrew Lim;Fan Wang

  • Affiliations:

  • Hong Kong University of Science and Technology;Hong Kong University of Science and Technology

  • Venue:
  • ICTAI '04 Proceedings of the 16th IEEE International Conference on Tools with Artificial Intelligence
  • Year:
  • 2004

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Abstract

In this paper, the Robust Graph Coloring Problem (RGCP), an extension of the classical graph coloring, is solved by various meta-heuristics. After discussing the search space encoding and neighborhood structure, several meta-heuristics including genetic algorithm, simulated annealing and tabu search are developed to solve RGCP. The experimental results on various sizes of input graph provide the performance of these meta-heuristics in terms of accuracy and run time.