A Novel Bi-objective Genetic Algorithm for the Graph Coloring Problem

Authors:
Lixia Han;Zhanli Han
Affiliations:
-;-
Venue:
ICCMS '10 Proceedings of the 2010 Second International Conference on Computer Modeling and Simulation - Volume 04
Year:
2010

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Characterization of graph properties for improved Pareto fronts using heuristics and EA for bi-objective graph coloring problem

Applied Soft Computing

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Abstract

Graph coloring problem is a classical NP-hard combinatorial optimization problem. In this paper, a new bi-objective model for the coloring problem is presented. Based on this new model, a bi-objective genetic algorithm is proposed which employs effective crossover and simple mutation operator as the genetic operators. The global convergence of the proposed algorithm to globally optimal set with probability one is proved. Experimental results demonstrate that the proposed algorithm is expected.