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dc.contributor.authorIvanova, Marika
dc.contributor.authorHaugland, Dag
dc.date.accessioned2020-08-12T13:19:04Z
dc.date.available2020-08-12T13:19:04Z
dc.date.issued2019
dc.PublishedIvanova M, Haugland D. Integer programming formulations for the shared multicast tree problem. Journal of combinatorial optimization. 2019;38(3):927-956eng
dc.identifier.issn1382-6905en_US
dc.identifier.issn1573-2886en_US
dc.identifier.urihttps://hdl.handle.net/1956/23696
dc.description.abstractWe study the shared multicast tree (SMT) problem in wireless networks. To support a multicast session between a set of network nodes, SMT aims to establish a wireless connection between them, such that the total energy consumption is minimized. All destinations of the multicast message must be connected, while non-destinations are optional nodes that can be used to relay messages. The objective function reflecting power consumption distinguishes SMT clearly from the traditional minimum Steiner tree problem. We develop two integer programming formulations for SMT. Both models are subsequently extended and strengthened. Theorems on relations between the LP bounds corresponding to the models are stated and proved. As the number of variables in the strongest formulations is a polynomial of degree four in the number of network nodes, the models are impractical for computing lower bounds in instances beyond a fairly small size, and therefore a constraint generation scheme is developed. Results from computational experiments with the models demonstrate good promise of the approaches taken.en_US
dc.language.isoengeng
dc.publisherSpringeren_US
dc.titleInteger Programming Formulations for the Shared Multicast Tree Problemen_US
dc.typePeer reviewed
dc.typeJournal article
dc.date.updated2020-01-17T14:05:00Z
dc.description.versionacceptedVersionen_US
dc.rights.holderCopyright Springer Science+Business Media, LLC, part of Springer Nature 2019en_US
dc.identifier.doihttps://doi.org/10.1007/s10878-019-00428-8
dc.identifier.cristin1776047
dc.source.journalJournal of combinatorial optimization


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