One of the nice things about genetic algorithms is that they can easily be used for a diverse array of problem domains, whereas PSO for example seems best-suited for candidates of real-valued vectors (although I am aware of the use of the latter in combinatorial problems). It has, however, occurred to me that, by using genetic algorithms because they are familiar and easy to apply, I could be forgoing a better solution with a different metaheuristic. To avoid subjective discussion, I am of course looking for carefully gathered empirical results about this subject matter. I can't seem to find too many on my own.
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