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Appears in Collections:Computing Science and Mathematics Book Chapters and Sections
Peer Review Status: Refereed
Title: A Classification of Hyper-heuristic Approaches
Authors: Burke, Edmund
Hyde, Matthew
Kendall, Graham
Ochoa, Gabriela
Ozcan, Ender
Woodward, John
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Editors: Gendreau, M
Potvin, J-Y
Citation: Burke E, Hyde M, Kendall G, Ochoa G, Ozcan E & Woodward J (2010) A Classification of Hyper-heuristic Approaches. In: Gendreau M, Potvin J-Y (ed.). Handbook of Metaheuristics. International Series in Operations Research & Management Science, 146, Berlin: Springer, pp. 449-468.
Issue Date: 2010
Publisher: Springer
Series/Report no.: International Series in Operations Research & Management Science, 146
Abstract: The current state of the art in hyper-heuristic research comprises a set of approaches that share the common goal of automating the design and adaptation of heuristic methods to solve hard computational search problems. The main goal is to produce more generally applicable search methodologies. In this chapter we present an overview of previous categorisations of hyper-heuristics and provide a unified classification and definition, which capture the work that is being undertaken in this field. We distinguish between two main hyper-heuristic categories: heuristic selection and heuristic generation. Some representative examples of each category are discussed in detail. Our goals are to clarify the mainfeatures of existing techniques and to suggest new directions for hyper-heuristic research.
Rights: The publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.
Type: Part of book or chapter of book
Affiliation: Computing Science and Mathematics
University of Nottingham
University of Nottingham
Computing Science - CSM Dept
University of Nottingham
Computing Science - CSM Dept

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