Abstract
The term “hyper-heuristics” is fairly new, although the notion has been hinted at in papers from time to time since the 1960s (e.g. Crowston et al., 1963). The key idea is to devise new algorithms for solving problems by combining known heuristics in ways that allow each to compensate, to some extent, for the weaknesses of others. They might be thought of as heuristics to choose heuristics. They are methods which work with a search space of heuristics. In this sense, they differ from most applications of metaheuristics (see Glover and Kochenberger, 2003) which usually work with search spaces of solutions. One of the main goals of research in this area is to devise algorithms that are fast and exhibit good performance across a whole family of problems, presumably because the algorithms address some shared features of the whole set of problems.
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Ross, P. (2005). Hyper-Heuristics. In: Burke, E.K., Kendall, G. (eds) Search Methodologies. Springer, Boston, MA. https://doi.org/10.1007/0-387-28356-0_17
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