Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/15758
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dc.contributor.authorBlazewicz, Jaceken_UK
dc.contributor.authorBurke, Edmunden_UK
dc.contributor.authorKendall, Grahamen_UK
dc.contributor.authorMruczkiewicz, Wojciechen_UK
dc.contributor.authorOguz, Ceydaen_UK
dc.contributor.authorSwiercz, Aleksandraen_UK
dc.date.accessioned2018-02-10T00:30:22Z-
dc.date.available2018-02-10T00:30:22Zen_UK
dc.date.issued2013-08en_UK
dc.identifier.urihttp://hdl.handle.net/1893/15758-
dc.description.abstractIn this paper we investigate the use of hyper-heuristic methodologies for predicting DNA sequences. In particular, we utilize Sequencing by Hybridization. We believe that this is the first time that hyper-heuristics have been investigated in this domain. A hyper-heuristic is provided with a set of low-level heuristics and the aim is to decide which heuristic to call at each decision point. We investigate three types of hyper-heuristics. Two of these (simulated annealing and tabu search) draw their inspiration from meta-heuristics. The choice function hyper-heuristic draws its inspiration from reinforcement learning. We utilize two independent sets of low-level heuristics. The first set is based on a previous tabu search method, with the second set being a significant extension to this basic set, including utilizing a different representation and introducing the definition of clusters. The datasets we use comprises two randomly generated datasets and also a publicly available biological dataset. In total, we carried out experiments using 70 different combinations of heuristics, using the three datasets mentioned above and investigating six different hyper-heuristic algorithms. Our results demonstrate the effectiveness of a hyper-heuristic approach to this problem domain. It is necessary to provide a good set of low-level heuristics, which are able to both intensify and diversify the search but this approach has demonstrated very encouraging results on this extremely difficult and important problem domain.en_UK
dc.language.isoenen_UK
dc.publisherSpringeren_UK
dc.relationBlazewicz J, Burke E, Kendall G, Mruczkiewicz W, Oguz C & Swiercz A (2013) A hyper-heuristic approach to sequencing by hybridization of DNA sequences. Annals of Operations Research, 207 (1), pp. 27-41. https://doi.org/10.1007/s10479-011-0927-yen_UK
dc.rightsThe 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.en_UK
dc.rights.urihttp://www.rioxx.net/licenses/under-embargo-all-rights-reserveden_UK
dc.subjectHyper-heuristicsen_UK
dc.subjectSimulated annealingen_UK
dc.subjectTabu searchen_UK
dc.subjectChoice functionen_UK
dc.subjectSequencing by hybridizationen_UK
dc.titleA hyper-heuristic approach to sequencing by hybridization of DNA sequencesen_UK
dc.typeJournal Articleen_UK
dc.rights.embargodate3000-01-01en_UK
dc.rights.embargoreason[A hyper-heuristic approach to sequencing by hybridization.pdf] The publisher does not allow this work to be made publicly available in this Repository therefore there is an embargo on the full text of the work.en_UK
dc.identifier.doi10.1007/s10479-011-0927-yen_UK
dc.citation.jtitleAnnals of Operations Researchen_UK
dc.citation.issn1572-9338en_UK
dc.citation.issn0254-5330en_UK
dc.citation.volume207en_UK
dc.citation.issue1en_UK
dc.citation.spage27en_UK
dc.citation.epage41en_UK
dc.citation.publicationstatusPublisheden_UK
dc.citation.peerreviewedRefereeden_UK
dc.type.statusVoR - Version of Recorden_UK
dc.author.emaile.k.burke@stir.ac.uken_UK
dc.citation.date31/07/2011en_UK
dc.contributor.affiliationPoznan University of Technologyen_UK
dc.contributor.affiliationComputing Science and Mathematics - Divisionen_UK
dc.contributor.affiliationUniversity of Nottinghamen_UK
dc.contributor.affiliationPoznan University of Technologyen_UK
dc.contributor.affiliationKoc Universityen_UK
dc.contributor.affiliationPoznan University of Technologyen_UK
dc.identifier.isiWOS:000321869500003en_UK
dc.identifier.scopusid2-s2.0-79959785617en_UK
dc.identifier.wtid695369en_UK
dcterms.dateAccepted2011-07-31en_UK
dc.date.filedepositdate2013-07-03en_UK
rioxxterms.typeJournal Article/Reviewen_UK
rioxxterms.versionVoRen_UK
local.rioxx.authorBlazewicz, Jacek|en_UK
local.rioxx.authorBurke, Edmund|en_UK
local.rioxx.authorKendall, Graham|en_UK
local.rioxx.authorMruczkiewicz, Wojciech|en_UK
local.rioxx.authorOguz, Ceyda|en_UK
local.rioxx.authorSwiercz, Aleksandra|en_UK
local.rioxx.projectInternal Project|University of Stirling|https://isni.org/isni/0000000122484331en_UK
local.rioxx.freetoreaddate3000-01-01en_UK
local.rioxx.licencehttp://www.rioxx.net/licenses/under-embargo-all-rights-reserved||en_UK
local.rioxx.filenameA hyper-heuristic approach to sequencing by hybridization.pdfen_UK
local.rioxx.filecount1en_UK
local.rioxx.source0254-5330en_UK
Appears in Collections:Computing Science and Mathematics Journal Articles

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