Evolution of hyperheuristics for the biobjective graph coloring problem using multiobjective genetic programming

Authors:
Paresh Tolay;Rajeev Kumar
Affiliations:
Indian Institute of Technology Kharagpur, Kharagpur, India;Indian Institute of Technology Kharagpur, Kharagpur, India
Venue:
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Year:
2009

Citing 3
Cited 0

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Enhancing solution quality of the biobjective graph coloring problem using hybridization of EA: biobjective graph coloring problem

Proceedings of the 10th annual conference on Genetic and evolutionary computation

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Abstract

We consider a formulation of the biobjective soft graph coloring problem so as to simultaneously minimize the number of colors used as well as the number of edges that connect vertices of the same color. We aim to evolve hyperheuristics for this class of problem using multiobjective genetic programming (MOGP). The major advantage being that these hyperheuristics can then be applied to any instance of this problem. We test the hyperheuristics on benchmark graph coloring problems, and in the absence of an actual Pareto-front, we compare the solutions obtained with existing heuristics. We then further improve the quality of hyperheuristics evolved, and try to make them closer to human-designed heuristics.