Hyper-heuristics.

Ross, Peter

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