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Hyper-heuristics.

Ross, Peter

Authors

Peter Ross



Contributors

Edmund Burke
Editor

Graham Kendall
Editor

Abstract

This chapter introduces and overviews an emerging methodology in search and optimisation. One of the key aims of these new approaches, which have been termed hyper-heuristics, is to raise the level of generality at which optimisation systems can operate. An objective is that hyper-heuristics will lead to more general systems that are able to handle a wide range of problem
domains rather than current meta-heuristic technology which tends to be customised to a particular problem or a narrow class of problems. Hyperheuristics are broadly concerned with intelligently choosing the right heuristic or algorithm in a given situation. Of course, a hyper-heuristic can be (often is) a (meta-)heuristic and it can operate on (meta-)heuristics. In a certain sense, a
hyper-heuristic works at a higher level when compared with the typical application of meta-heuristics to optimisation problems i.e. a hyper-heuristic could be thought of as a (meta)-heuristic which operates on lower level (meta-)heuristics. In this chapter we will introduce the idea and give a brief history of this emerging area. In addition, we will review some of the latest work to be published in the field.

Citation

Ross, P. (2005). Hyper-heuristics. In E. Burke, & G. Kendall (Eds.), Search Methodologies: Introductory Tutorials in Optimization and Decision Support Techniques (529-556). Springer-Verlag

Publication Date 2005
Deposit Date Jun 23, 2008
Peer Reviewed Peer Reviewed
Pages 529-556
Book Title Search Methodologies: Introductory Tutorials in Optimization and Decision Support Techniques
ISBN 978-0387234601
Keywords Hyper-heuristic; meta-heuristic; heuristic; optimisation; search;
Public URL http://researchrepository.napier.ac.uk/id/eprint/1845