Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/18264
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dc.contributor.authorLopez-Camacho, Euniceen_UK
dc.contributor.authorTerashima-Marin, Hugoen_UK
dc.contributor.authorOchoa, Gabrielaen_UK
dc.contributor.authorConant-Pablos, Santiago Enriqueen_UK
dc.date.accessioned2014-10-31T23:50:55Z-
dc.date.available2014-10-31T23:50:55Z-
dc.date.issued2013-10en_UK
dc.identifier.urihttp://hdl.handle.net/1893/18264-
dc.description.abstractThis paper uses a knowledge discovery method, Principal Component Analysis (PCA), to gain a deeper understanding of the structure of bin packing problems and how this relates to the performance of heuristic approaches to solve them. The study considers six heuristics and their combination through an evolutionary hyper-heuristic framework. A wide set of problem instances is considered, including one-dimensional and two-dimensional regular and irregular problems. A number of problem features are considered, which are reduced to the subset of nine features that more strongly relate with heuristic performance. PCA is used to further reduce the dimensionality of the instance features and produce 2D maps. The performance of the heuristics and hyper-heuristics is then super-imposed into these maps to visually reveal relationships between problem features and heuristic behavior. Our analysis indicates that some instances are clearly harder to solve than others for all the studied heuristics and hyper-heuristics. The PCA maps give a valuable indication of the combination of features characterizing easy and hard to solve instances. We found indeed correlations between instance features and heuristic performance. The so-called DJD heuristics are able to best solve a large proportion of instances, but simpler and faster heuristics can outperform them in some cases. In particular when solving 1D instances with low number of pieces, and, more surprisingly, when solving some difficult 2D instances with small areas with low variability. This analysis can be generalized to other problem domains where a set of features characterize instances and several problem solving heuristics are available.en_UK
dc.language.isoenen_UK
dc.publisherElsevieren_UK
dc.relationLopez-Camacho E, Terashima-Marin H, Ochoa G & Conant-Pablos SE (2013) Understanding the structure of bin packing problems through principal component analysis. International Journal of Production Economics, 145 (2), pp. 488-499. https://doi.org/10.1016/j.ijpe.2013.04.041en_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.subjectHeuristicsen_UK
dc.subjectHyper-heuristicsen_UK
dc.subjectBin packing problemen_UK
dc.subjectPrincipal component analysisen_UK
dc.subjectAlgorithm selectionen_UK
dc.subjectKnowledge discoveryen_UK
dc.titleUnderstanding the structure of bin packing problems through principal component analysisen_UK
dc.typeJournal Articleen_UK
dc.rights.embargodate3000-01-01en_UK
dc.rights.embargoreason[1-s2.0-S0925527313002053-main.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.doi10.1016/j.ijpe.2013.04.041en_UK
dc.citation.jtitleInternational Journal of Production Economicsen_UK
dc.citation.issn0925-5273en_UK
dc.citation.volume145en_UK
dc.citation.issue2en_UK
dc.citation.spage488en_UK
dc.citation.epage499en_UK
dc.citation.publicationstatusPublisheden_UK
dc.citation.peerreviewedRefereeden_UK
dc.type.statusVoR - Version of Recorden_UK
dc.author.emailgabriela.ochoa@stir.ac.uken_UK
dc.contributor.affiliationMonterrey Institute of Technology and Higher Education (Tecnológico de Monterrey)en_UK
dc.contributor.affiliationMonterrey Institute of Technology and Higher Education (Tecnológico de Monterrey)en_UK
dc.contributor.affiliationComputing Scienceen_UK
dc.contributor.affiliationMonterrey Institute of Technology and Higher Education (Tecnológico de Monterrey)en_UK
dc.identifier.isiWOS:000324844300005en_UK
dc.identifier.scopusid2-s2.0-84878009527en_UK
dc.identifier.wtid699938en_UK
dc.contributor.orcid0000-0001-7649-5669en_UK
dcterms.dateAccepted2013-10-31en_UK
dc.date.filedepositdate2014-01-13en_UK
rioxxterms.typeJournal Article/Reviewen_UK
rioxxterms.versionVoRen_UK
local.rioxx.authorLopez-Camacho, Eunice|en_UK
local.rioxx.authorTerashima-Marin, Hugo|en_UK
local.rioxx.authorOchoa, Gabriela|0000-0001-7649-5669en_UK
local.rioxx.authorConant-Pablos, Santiago Enrique|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.filename1-s2.0-S0925527313002053-main.pdfen_UK
local.rioxx.filecount1en_UK
local.rioxx.source0925-5273en_UK
Appears in Collections:Computing Science and Mathematics Journal Articles

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