Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/20746
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dc.contributor.authorLopez-Camacho, Eunice-
dc.contributor.authorTerashima-Marin, Hugo-
dc.contributor.authorRoss, Peter-
dc.contributor.authorOchoa, Gabriela-
dc.date.accessioned2014-10-31T23:20:30Z-
dc.date.issued2014-11-
dc.identifier.urihttp://hdl.handle.net/1893/20746-
dc.description.abstractOne- and two-dimensional packing and cutting problems occur in many commercial contexts, and it is often important to be able to get good-quality solutions quickly. Fairly simple deterministic heuristics are often used for this purpose, but such heuristics typically find excellent solutions for some problems and only mediocre ones for others. Trying several different heuristics on a problem adds to the cost. This paper describes a hyper-heuristic methodology that can generate a fast, deterministic algorithm capable of producing results comparable to that of using the best problem-specific heuristic, and sometimes even better, but without the cost of trying all the heuristics. The generated algorithm handles both one- and two-dimensional problems, including two-dimensional problems that involve irregular concave polygons. The approach is validated using a large set of 1417 such problems, including a new benchmark set of 480 problems that include concave polygons.en_UK
dc.language.isoen-
dc.publisherElsevier-
dc.relationLopez-Camacho E, Terashima-Marin H, Ross P & Ochoa G (2014) A unified hyper-heuristic framework for solving bin packing problems, Expert Systems with Applications, 41 (15), pp. 6876-6889.-
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.-
dc.subjectBin packing problemsen_UK
dc.subjectEvolutionary computationen_UK
dc.subjectHyper-heuristicsen_UK
dc.subjectHeuristicsen_UK
dc.subjectOptimizationen_UK
dc.titleA unified hyper-heuristic framework for solving bin packing problemsen_UK
dc.typeJournal Articleen_UK
dc.rights.embargodate2999-12-31T00:00:00Z-
dc.rights.embargoreasonThe 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.-
dc.identifier.doihttp://dx.doi.org/10.1016/j.eswa.2014.04.043-
dc.citation.jtitleExpert Systems with Applications-
dc.citation.issn0957-4174-
dc.citation.volume41-
dc.citation.issue15-
dc.citation.spage6876-
dc.citation.epage6889-
dc.citation.publicationstatusPublished-
dc.citation.peerreviewedRefereed-
dc.type.statusPublisher version (final published refereed version)-
dc.author.emailgabriela.ochoa@stir.ac.uk-
dc.contributor.affiliationMonterrey Institute of Technology and Higher Education (Tecnológico de Monterrey)-
dc.contributor.affiliationMonterrey Institute of Technology and Higher Education (Tecnológico de Monterrey)-
dc.contributor.affiliationEdinburgh Napier University-
dc.contributor.affiliationComputing Science - CSM Dept-
dc.rights.embargoterms2999-12-31-
dc.rights.embargoliftdate2999-12-31-
dc.identifier.isi000339694400030-
Appears in Collections:Computing Science and Mathematics Journal Articles

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