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A classification of hyper-heuristic approaches: Revisited

Burke, Edmund K.; Hyde, Matthew R.; Kendall, Graham; Ochoa, Gabriela; Özcan, Ender; Woodward, John R.


Edmund K. Burke

Matthew R. Hyde

Graham Kendall

Gabriela Ochoa

John R. Woodward


© Springer International Publishing AG, part of Springer Nature 2019. 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.


Burke, E. K., Hyde, M. R., Kendall, G., Ochoa, G., Özcan, E., & Woodward, J. R. (2019). A classification of hyper-heuristic approaches: Revisited. In Handbook of metaheuristics (453-477). Cham: Springer Publishing Company.

Acceptance Date Oct 1, 2018
Online Publication Date Sep 21, 2018
Publication Date Jan 1, 2019
Deposit Date Oct 14, 2018
Publicly Available Date Oct 15, 2018
Journal International Series in Operations Research and Management Science
Electronic ISSN 2214-7934
Publisher Springer Publishing Company
Volume 272
Pages 453-477
Series Title International Series in Operations Research & Management Science
Series Number 272
Series ISSN 2214-7934
Book Title Handbook of metaheuristics
Chapter Number 14
ISBN 9783319910857
Public URL
Publisher URL
Additional Information Burke E.K., Hyde M.R., Kendall G., Ochoa G., Özcan E., Woodward J.R. (2019) A Classification of Hyper-Heuristic Approaches: Revisited. In: Gendreau M., Potvin JY. (eds) Handbook of Metaheuristics. International Series in Operations Research & Management Science, vol 272. Springer, Cham


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