  Firefly algorithms belong to modern meta-heuristic algorithms inspired by
nature that can be successfully applied to continuous optimization problems. In
this paper, we have been applied the firefly algorithm, hybridized with local
search heuristic, to combinatorial optimization problems, where we use graph
3-coloring problems as test benchmarks. The results of the proposed memetic
firefly algorithm (MFFA) were compared with the results of the Hybrid
Evolutionary Algorithm (HEA), Tabucol, and the evolutionary algorithm with SAW
method (EA-SAW) by coloring the suite of medium-scaled random graphs (graphs
with 500 vertices) generated using the Culberson random graph generator. The
results of firefly algorithm were very promising and showed a potential that
this algorithm could successfully be applied in near future to the other
combinatorial optimization problems as well.
