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dc.contributor.authorBorthen, Thomas
dc.contributor.authorLoennechen, Henrik
dc.contributor.authorWang, Xin
dc.contributor.authorFagerholt, Kjetil
dc.contributor.authorVidal, Thibaut
dc.date.accessioned2017-11-10T12:00:31Z
dc.date.available2017-11-10T12:00:31Z
dc.date.created2017-08-22T21:04:13Z
dc.date.issued2017
dc.identifier.citationEURO Journal on Transportation and Logistics. 2017, .nb_NO
dc.identifier.issn2192-4376
dc.identifier.urihttp://hdl.handle.net/11250/2465540
dc.description.abstractThis paper introduces a genetic search-based heuristic to solve an offshore supply vessel planning problem (SVPP) faced by the Norwegian oil and gas company Statoil. The aim is to help the company in determining the optimal size of supply vessels to charter in and their corresponding voyages and schedules. We take inspiration from the hybrid genetic search with adaptive diversity control (HGSADC) algorithm of Vidal et al. (Oper Res 60(3):611–624, 2012), which successfully addresses a large class of vehicle routing problems, including the multi-period VRP (PVRP), and adapt it to account for some special features that are recurrent in maritime transportation but scarcely found in classical PVRPs, in particular, the possibility of having voyages spanning over multiple time periods in the planning horizon. Our computational experiments show that the proposed heuristic is scalable and stable, being able to solve industrial SVPPs of realistic size while significantly outperforming the existing approaches.nb_NO
dc.language.isoengnb_NO
dc.publisherSpringer Verlagnb_NO
dc.titleA genetic search-based heuristic for a fleet size and periodic routing problem with application to offshore supply planningnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionacceptedVersionnb_NO
dc.source.pagenumber30nb_NO
dc.source.journalEURO Journal on Transportation and Logisticsnb_NO
dc.identifier.doi10.1007/s13676-017-0111-x
dc.identifier.cristin1488021
dc.relation.projectNorges forskningsråd: 235518nb_NO
dc.description.localcode© Springer Verlag. LOCKED until 22.8.2018 due to copyright restrictions. The final publication is available at https://link.springer.com/article/10.1007%2Fs13676-017-0111-x. This is the authors' accepted and refereed manuscript to the article.nb_NO
cristin.unitcode194,60,25,0
cristin.unitnameInstitutt for industriell økonomi og teknologiledelse
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1


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