It is widely acknowledged that some of the most powerful algorithms for graph coloring involve the combination of evolutionary-based methods with exploitative local search-based techniques. This chapter conducts a review and discussion of such methods, principally focussing on the role that recombination plays in this process. In particular we observe that, while in some cases recombination seems to be usefully combining substructures inherited from parents, in other cases it is merely acting as a macro perturbation operator, helping to reinvigorate the search from time to time.


Local Search Tabu Search Graph Coloring Greedy Randomize Adaptive Search Procedure Color Classis 
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.

evolutionary algorithm


grouping genetic algorithm


greedy partition crossover


greedy randomized adaptive search procedure


random access memory


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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.School of MathematicsCardiff UniversityCardiffUK

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