dc.contributor.author | Kheiri, A | |
dc.contributor.author | Keedwell, Edward | |
dc.contributor.author | Gibson, M | |
dc.contributor.author | Savić, Dragan | |
dc.date.accessioned | 2016-03-11T09:53:59Z | |
dc.date.issued | 2015-09-01 | |
dc.description.abstract | Hyper-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.sponsorship | The authors would like to gratefully acknowledge the support of the EPSRC under Grant No: EP/K000519/1 | en_GB |
dc.identifier.citation | Vol. 119, pp. 1269–1277 | en_GB |
dc.identifier.doi | 10.1016/j.proeng.2015.08.993 | |
dc.identifier.uri | http://hdl.handle.net/10871/20669 | |
dc.language.iso | en | en_GB |
dc.publisher | Elsevier | en_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.subject | Hyper-heuristic | en_GB |
dc.subject | Water Distribution Network | en_GB |
dc.subject | Hidden Markov Model | en_GB |
dc.title | Sequence analysis-based hyper-heuristics for water distribution network optimisation | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2016-03-11T09:53:59Z | |
dc.description | 13th Computer Control for Water Industry Conference, CCWI 2015 | en_GB |
dc.identifier.journal | Procedia Engineering | en_GB |