A symmetry-breaking approach of the graph coloring problem with GAs

The graph coloring problem (GCP) is a well known combinatorial problem with a highly symmetric solution space. Population-based approaches do not provide a good alternative because of the danger of recombining good individuals from different regions of the search space to produce poor offspring. This work introduces the symmetry of the graph coloring problem with genetic algorithms and presents a genetic algorithm that breaks the symmetry of GCP by cyclic permutations.