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dc.contributor.authorMatoušek, Radomilcs
dc.contributor.authorDobrovský, Ladislavcs
dc.contributor.authorKůdela, Jakubcs
dc.date.accessioned2022-01-11T11:54:33Z
dc.date.available2022-01-11T11:54:33Z
dc.date.issued2021-12-31cs
dc.identifier.citationInternational Journal of Industrial Engineering Computations. 2021, vol. 13, issue 2, p. 151-164.en
dc.identifier.issn1923-2934cs
dc.identifier.other175648cs
dc.identifier.urihttp://hdl.handle.net/11012/203280
dc.description.abstractThe Quadratic Assignment Problem (QAP) is one of the classical combinatorial optimization problems and is known for its diverse applications. The QAP is an NP-hard optimization problem which attracts the use of heuristic or metaheuristic algorithms that can find quality solutions in an acceptable computation time. On the other hand, there is quite a broad spectrum of mathematical programming techniques that were developed for finding the lower bounds for the QAP. This paper presents a fusion of the two approaches whereby the solutions from the computations of the lower bounds are used as the starting points for a metaheuristic, called HC12, which is implemented on a GPU CUDA platform. We perform extensive computational experiments that demonstrate that the use of these lower bounding techniques for the construction of the starting points has a significant impact on the quality of the resulting solutions.en
dc.formattextcs
dc.format.extent151-164cs
dc.format.mimetypeapplication/pdfcs
dc.language.isoencs
dc.publisherGrowing Sciencecs
dc.relation.ispartofInternational Journal of Industrial Engineering Computationscs
dc.relation.urihttp://www.growingscience.com/ijiec/Vol13/IJIEC_2021_33.pdfcs
dc.rightsCreative Commons Attribution 4.0 Internationalcs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectHeuristicsen
dc.subjectLower boundsen
dc.subjectMetaheuristicsen
dc.subjectQuadratic assignment problemen
dc.subjectStarting valuesen
dc.titleHow to start a heuristic? Utilizing lower bounds for solving the quadratic assignment problemen
thesis.grantorVysoké učení technické v Brně. Fakulta strojního inženýrství. Ústav automatizace a informatikycs
sync.item.dbidVAV-175648en
sync.item.dbtypeVAVen
sync.item.insts2022.03.02 12:54:42en
sync.item.modts2022.03.02 12:15:05en
dc.coverage.issue2cs
dc.coverage.volume13cs
dc.identifier.doi10.5267/j.ijiec.2021.12.003cs
dc.rights.accessopenAccesscs
dc.rights.sherpahttp://www.sherpa.ac.uk/romeo/issn/1923-2934/cs
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen


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Creative Commons Attribution 4.0 International
Except where otherwise noted, this item's license is described as Creative Commons Attribution 4.0 International