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.",
notes = "GECCO-2009 A joint meeting of the eighteenth
international conference on genetic algorithms
(ICGA-2009) and the fourteenth annual genetic
programming conference (GP-2009).