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Thanks, appreciated!

The difference between meta-heuristics and hyper-heuristics is that the former is a much broader concept, including such things as genetic algorithms. Hyper-heuristics is specifically about selecting among heuristics, which excludes e.g. evolutionary algorithms. Graham Kendall, one of the inventors of the concept, explains that they would have called it meta-heuristics if that name was not already taken.

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... so hyper heuristics is meta-heuristics except leaving out one of your most promising options -- genetic algorithms? Or just refusing to use that at the meta stage? The difference still seems dubious. Your paper with the grid includes genetic algorithms to select from, so I guess it is not using GA at the meta level. Hyper as in a hypercube selection space of options? Maybe not because you use a decision tree for selection. It seems like the field could benefit from a regularization of terms. I still don't see what separates it from meta heuristics except for a name the limitations don't seem established. It seems hyper-heuristics is to meta-heuristics like the cloud is to network computing. Market speak does change -- not much you can do about that. The terminology is a nitpick -- fascinating papers.

Meta-heuristics as conceptualized by many (most?) does not include selection among algorithms. Hyper-heuristics does. It's fine if some of the algorithms selected among are meta-heuristics. Yes, this is very confusing, and yes, better terminology is needed. In particular, we should probably stop using the term meta-heuristics, because it has too many incompatible meanings.

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