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dc.contributor.authorNafstad, Gaute Messel
dc.contributor.authorHaugseth, Amund
dc.contributor.authorHøyland, Vebjørn
dc.contributor.authorStålhane, Magnus
dc.date.accessioned2021-01-11T09:04:15Z
dc.date.available2021-01-11T09:04:15Z
dc.date.created2021-01-05T11:08:40Z
dc.date.issued2020
dc.identifier.issn0305-0548
dc.identifier.urihttps://hdl.handle.net/11250/2722282
dc.description.abstractThis paper studies the problem of creating an optimal flight schedule for a heterogeneous fleet of helicopters tasked with transporting personnel to, from, and between offshore installations. The problem can be modelled as a rich vehicle routing problem and combines the following properties from the vehicle routing literature: pickup and delivery structure, heterogeneous fleet operating out of multiple depots, multi-trip, and temporal synchronization of transportation tasks. We present compact and extended mathematical models of the problem, where the extended model is based on generating all trips apriori. When solving the extended model we apply delayed constraint generation (DCG) to parts of the model to speed up the solution process. Computational results are presented that show that the extended formulation and solution method can solve realistic instances of the problem within one hour. The results further show that the DCG method works significantly better than using lazy constraints from a commercial solver, especially when the number of transportation tasks requiring temporal synchronization becomes large.en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleAn exact solution method for a rich helicopter flight scheduling problem arising in offshore oil and gas logisticsen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.source.journalComputers & Operations Researchen_US
dc.identifier.doi10.1016/j.cor.2020.105158
dc.identifier.cristin1865381
dc.description.localcode(C) 2020 The Author(s). Published by Elsevier Ltd.This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).en_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2


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