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dc.contributor.authorChristiansen, Marielle
dc.contributor.authorFagerholt, Kjetil
dc.contributor.authorRachaniotis, Nikolaos P.
dc.contributor.authorTveit, Ingeborg
dc.contributor.authorØverdal, Marte Viktoria
dc.date.accessioned2018-03-05T12:45:17Z
dc.date.available2018-03-05T12:45:17Z
dc.date.created2015-12-02T13:32:50Z
dc.date.issued2015
dc.identifier.isbn978-3-319-24263-7
dc.identifier.urihttp://hdl.handle.net/11250/2488638
dc.description.abstractWe consider a real fuel supply vessel routing and scheduling problem faced by a Hellenic oil company with a given fleet of fuel supply vessels used to supply customer ships outside Piraeus Port. The supply vessels are loading fuel at refineries in the port area before delivering it to a given set of customer ships within specified time windows. A customer ship may place orders of more than one fuel type, and all orders placed by a customer ship do not have to be serviced by the same vessel, meaning customer splitting is possible. Fuel transported to the customer ships is allocated to compartments on board the supply vessels, and fuels of different types cannot be mixed in the same compartment. The objective is to design routes and schedules for the supply vessels while maximizing the company’s profit. We propose a mixed-integer programming (MIP) model for the problem and provide a computational study based on real instances.nb_NO
dc.language.isoengnb_NO
dc.publisherSpringernb_NO
dc.relation.ispartofComputational Logistics : 6th International Conference, ICCL 2015, Delft, The Netherlands, September 23-25, 2015, Proceedings
dc.titleA Decision Support Model for Routing and Scheduling a Fleet of Fuel Supply Vesselsnb_NO
dc.typeChapternb_NO
dc.description.versionacceptedVersionnb_NO
dc.source.pagenumber46-60nb_NO
dc.identifier.doi10.1007/978-3-319-24264-4_4
dc.identifier.cristin1296059
dc.relation.projectNorges forskningsråd: 205298nb_NO
dc.description.localcodeThis is a post-peer-review, pre-copyedit version of a chapter published in [International Conference on Computational Logistics]. The final authenticated version is available online at: https://link.springer.com/chapter/10.1007%2F978-3-319-24264-4_4nb_NO
cristin.unitcode194,60,25,0
cristin.unitnameInstitutt for industriell økonomi og teknologiledelse
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1


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