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Five Phase and Genetic Hive Hyper-Heuristics for the Cross-Domain Search

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7219))

Abstract

In this paper we present two hyper-heuristics: Five Phase Approach (5Ph) and Genetic Hive (GH), developed for the Cross-Domain Heuristic Search Challenge held in 2011. Performance of both methods is studied. Experience gained in construction of the hyper-heuristics is presented. Conclusions and recommendations for the future advancement of hyper-heuristic methodologies are discussed.

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References

  1. Burke, E., Curtois, T., Hyde, M., Ochoa, G., Vazquez-Rodriguez, J.A.: HyFlex: A Benchmark Framework for Cross-domain Heuristic Search. ArXiv e-prints (2011), http://adsabs.harvard.edu/abs/2011arXiv1107.5462B

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  4. Hyde, M., Ochoa, G., Parkes, A.: Cross-domain Heuristic Search Challenge (2011) http://www.asap.cs.nott.ac.uk/chesc2011/

  5. Hyde, M., Ochoa, G.: ASAP Default Hyper-heuristics (2011) http://www.asap.cs.nott.ac.uk/chesc2011/defaulthh.html

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© 2012 Springer-Verlag Berlin Heidelberg

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Cichowicz, T., Drozdowski, M., Frankiewicz, M., Pawlak, G., Rytwiński, F., Wasilewski, J. (2012). Five Phase and Genetic Hive Hyper-Heuristics for the Cross-Domain Search. 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_27

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  • DOI: https://doi.org/10.1007/978-3-642-34413-8_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34412-1

  • Online ISBN: 978-3-642-34413-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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