Abstract
This paper describes a new hyperheuristic algorithm that performs well over a variety of different problem classes. A novel method for switching between working on a single solution and a pool of solutions is proposed. This method is combined with an adaptive strategy that guides the selection of the underlying low-level heuristics throughout the search. The algorithm was implemented based on the HyFlex framework and was submitted as a candidate for the Cross-Domain Heuristic Search Challenge 2011.
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References
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Lehrbaum, A., Musliu, N. (2012). A New Hyperheuristic Algorithm for Cross-Domain Search Problems. In: Hamadi, Y., Schoenauer, M. (eds) Learning and Intelligent Optimization. LION 2012. Lecture Notes in Computer Science, vol 7219. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34413-8_41
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DOI: https://doi.org/10.1007/978-3-642-34413-8_41
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34412-1
Online ISBN: 978-3-642-34413-8
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