dc.contributor.author | Gutierrez-Alcoba, Alejandro | |
dc.contributor.author | Ortega, Gloria | |
dc.contributor.author | Hendrix, Eligius M.T. | |
dc.contributor.author | Halvorsen-Weare, Elin Espeland | |
dc.contributor.author | Haugland, Dag | |
dc.date.accessioned | 2017-11-07T12:06:48Z | |
dc.date.available | 2017-11-07T12:06:48Z | |
dc.date.issued | 2017 | |
dc.Published | Gutierrez-Alcoba, Ortega, Hendrix EM, Halvorsen-Weare EEH, Haugland D. A model for optimal fleet composition of vessels for offshore wind farm maintenance. Procedia Computer Science. 2017;108:1512-1521 | eng |
dc.identifier.issn | 1877-0509 | en_US |
dc.identifier.uri | https://hdl.handle.net/1956/16878 | |
dc.description.abstract | We present a discrete optimisation model that chooses an optimal fleet of vessels to support maintenance operations at Offshore Wind Farms (OFWs). The model is presented as a bi-level problem. On the first (tactical) level, decisions are made on the fleet composition for a certain time horizon. On the second (operational) level, the fleet is used to optimise the schedule of operations needed at the OWF, given events of failures and weather conditions. | en_US |
dc.language.iso | eng | eng |
dc.publisher | Elsevier | en_US |
dc.rights | Attribution CC BY-NC-ND | eng |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | eng |
dc.subject | Offshore Wind Farms | eng |
dc.subject | Decision Support System | eng |
dc.subject | Fleet composition | eng |
dc.subject | Maintenance planning | eng |
dc.title | A model for optimal fleet composition of vessels for offshore wind farm maintenance | en_US |
dc.type | Peer reviewed | |
dc.type | Journal article | |
dc.date.updated | 2017-10-06T06:13:02Z | |
dc.description.version | publishedVersion | en_US |
dc.rights.holder | Copyright 2017 The Author(s) | en_US |
dc.identifier.doi | https://doi.org/10.1016/j.procs.2017.05.230 | |
dc.identifier.cristin | 1502402 | |
dc.source.journal | Procedia Computer Science | |
dc.relation.project | Norges forskningsråd: 193823 | |