Minimum-Volume Covering Ellipsoids: Improving the Efficiency of the Wolfe-Atwood Algorithm for Large-Scale Instances by Pooling and Batching

dc.contributor.authorKudela, Jakub
dc.coverage.issue2cs
dc.coverage.volume25cs
dc.date.accessioned2020-05-05T07:21:11Z
dc.date.available2020-05-05T07:21:11Z
dc.date.issued2019-12-20cs
dc.description.abstractThe Minimum-Volume Covering Ellipsoid (MVCE) problem is an important optimization problem that comes up in various areas of engineering and statistics. In this paper, we improve the state-of-the-art Wolfe-Atwood algorithm for solving the MVCE problem with pooling and batching procedures. This implementation yields significant improvements on the runtime of the algorithm for large-scale instances of the MVCE problem, which is demonstrated on quite extensive computational experiments.en
dc.formattextcs
dc.format.extent19-26cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationMendel. 2019 vol. 25, č. 2, s. 19-26. ISSN 1803-3814cs
dc.identifier.doi10.13164/mendel.2019.2.019en
dc.identifier.issn2571-3701
dc.identifier.issn1803-3814
dc.identifier.urihttp://hdl.handle.net/11012/187000
dc.language.isoencs
dc.publisherInstitute of Automation and Computer Science, Brno University of Technologycs
dc.relation.ispartofMendelcs
dc.relation.urihttps://mendel-journal.org/index.php/mendel/article/view/104cs
dc.rightsCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International licenseen
dc.rights.accessopenAccessen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0en
dc.subjectminimum-volume covering ellipsoiden
dc.subjectLowner-John ellipsoiden
dc.subjectlarge-scale optimizationen
dc.subjectWolfe-Atwood algorithmen
dc.subjectpoolingen
dc.subjectbatchingen
dc.titleMinimum-Volume Covering Ellipsoids: Improving the Efficiency of the Wolfe-Atwood Algorithm for Large-Scale Instances by Pooling and Batchingen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.facultyFakulta strojního inženýrstvícs
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