Contemporary Methods for Graph Coloring as an Example of Discrete Optimization

Adrian Bilski


This paper provides an insight into graph coloring
application of the contemporary heuristic methods. It discusses a
variety of algorithmic solutions for The Graph Coloring Problem
(GCP) and makes recommendations for implementation. The
GCP is the NP-hard problem, which aims at finding the minimum
number of colors for vertices in such a way, that none of two
adjacent vertices are marked with the same color.With the advent
of multicore processing technology, the metaheuristic approach
to solving GCP reemerged as means of discrete optimization. To
explain the phenomenon of these methods, the author makes a
thorough survey of AI-based algorithms for GCP, while pointing
out the main differences between all these techniques.

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