A Classification of Hyper-Heuristic Approaches: Revisited

Edmund K. Burke (), Matthew R. Hyde (), Graham Kendall (), Gabriela Ochoa (), Ender Özcan () and John R. Woodward ()
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Edmund K. Burke: University of Leicester
Matthew R. Hyde: University of Nottingham
Graham Kendall: University of Nottingham Malaysia Campus
Gabriela Ochoa: University of Stirling
Ender Özcan: University of Nottingham
John R. Woodward: Queen Mary University of London

Chapter Chapter 14 in Handbook of Metaheuristics, 2019, pp 453-477 from Springer

Abstract: Abstract Hyper-heuristics comprise a set of approaches that aim to automate the development of computational search methodologies. This chapter overviews previous categorisations of hyper-heuristics and provides a unified classification and definition. We distinguish between two main hyper-heuristic categories: heuristic selection and heuristic generation. Some representative examples of each category are discussed in detail and recent research trends are highlighted.

Keywords: Hyper-heuristic Research; Heuristic Selection; General Heuristics; Heuristic Search Space; Construction Heuristics (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/978-3-319-91086-4_14

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