Please use this identifier to cite or link to this item: http://hdl.handle.net/10773/17238
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dc.contributor.authorFortz, Bernardpt
dc.contributor.authorRequejo, Cristinapt
dc.contributor.authorOliveira, Olgapt
dc.date.accessioned2017-04-13T15:17:13Z-
dc.date.available2018-07-20T14:01:00Z-
dc.date.issued2017-01-
dc.identifier.issn0377-2217pt
dc.identifier.urihttp://hdl.handle.net/10773/17238-
dc.description.abstractThe Minimum Weighted Tree Reconstruction (MWTR) problem consists of finding a minimum length weighted tree connecting a set of terminal nodes in such a way that the length of the path between each pair of terminal nodes is greater than or equal to a given distance between the considered pair of terminal nodes. This problem has applications in several areas, namely, the inference of phylogenetic trees, the modeling of traffic networks and the analysis of internet infrastructures. In this paper, we investigate the MWTR problem and we present two compact mixed-integer linear programming models to solve the problem. Computational results using two different sets of instances, one from the phylogenetic area and another from the telecommunications area, show that the best of the two models is able to solve instances of the problem having up to 15 terminal nodes.pt
dc.language.isoengpt
dc.publisherElsevierpt
dc.relationFCT - UID/MAT/04106/2013pt
dc.relationFCT - SFRH/BD/-76268/2011pt
dc.relationInteruniversity Attraction Poles Programme P7/36 <<COMEX>>pt
dc.rightsopenAccesspor
dc.subjectMixed integer linear programmingpt
dc.subjectDistance matrixpt
dc.subjectTree realizationpt
dc.subjectTopology discoverypt
dc.subjectRouting topology inferencept
dc.subjectBalanced minimum evolution problempt
dc.subjectMinimum evolution problempt
dc.titleCompact mixed integer linear programming models to the Minimum Weighted Tree Reconstruction problempt
dc.typearticlept
dc.peerreviewedyespt
ua.distributioninternationalpt
degois.publication.firstPage242pt
degois.publication.issue1pt
degois.publication.lastPage251pt
degois.publication.titleEuropean Journal of Operational Researchpt
degois.publication.volume256pt
dc.date.embargo2018-01-01T16:00:00Z-
dc.identifier.doi10.1016/j.ejor.2016.06.014pt
Appears in Collections:CIDMA - Artigos
OGTCG - Artigos

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