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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.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.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.
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.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.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.citation.jtitleAnnals of Operations Researchen_UK
dc.type.statusVoR - Version of Recorden_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
rioxxterms.typeJournal Article/Reviewen_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|
local.rioxx.filenameA hyper-heuristic approach to sequencing by hybridization.pdfen_UK
Appears in Collections:Computing Science and Mathematics Journal Articles

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