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dc.contributor.authorKheiri, A
dc.contributor.authorKeedwell, Edward
dc.contributor.authorGibson, M
dc.contributor.authorSavić, Dragan
dc.date.accessioned2016-03-11T09:53:59Z
dc.date.issued2015-09-01
dc.description.abstractHyper-heuristics operate at the level above traditional (meta-)heuristics that ‘optimise the optimiser’. These algorithms can combine low level heuristics to create bespoke algorithms for particular classes of problems. The lowlevel heuristics can be mutation operators or hill climbing algorithms and can include industry expertise. This paper investigates the use of a new hyper-heuristic basedon sequence analysis in the biosciences, to develop new optimisers that can outperform conventional evolutionary approaches. It demonstrates that the new algorithms develop high quality solutions on benchmark water distribution network optimisation problems efficiently, and can yield important information about the problem search space.en_GB
dc.description.sponsorshipThe authors would like to gratefully acknowledge the support of the EPSRC under Grant No: EP/K000519/1en_GB
dc.identifier.citationVol. 119, pp. 1269–1277en_GB
dc.identifier.doi10.1016/j.proeng.2015.08.993
dc.identifier.urihttp://hdl.handle.net/10871/20669
dc.language.isoenen_GB
dc.publisherElsevieren_GB
dc.rights© 2015 The Authors. Published by Elsevier. This is an open access article published under the CC BY-NC-ND license: http://creativecommons.org/licenses/by-nc-nd/4.0/en_GB
dc.subjectHyper-heuristicen_GB
dc.subjectWater Distribution Networken_GB
dc.subjectHidden Markov Modelen_GB
dc.titleSequence analysis-based hyper-heuristics for water distribution network optimisationen_GB
dc.typeArticleen_GB
dc.date.available2016-03-11T09:53:59Z
dc.description13th Computer Control for Water Industry Conference, CCWI 2015en_GB
dc.identifier.journalProcedia Engineeringen_GB


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