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dc.contributor.authorBye, Robin Trulssen
dc.contributor.authorSchaathun, Hans Georg
dc.date.accessioned2018-05-24T09:12:01Z
dc.date.available2018-05-24T09:12:01Z
dc.date.created2016-01-26T11:46:52Z
dc.date.issued2015
dc.identifier.isbn978-3-319-27680-9
dc.identifier.urihttp://hdl.handle.net/11250/2499053
dc.description.abstractTug fleet optimisation algorithms can be designed to solve the problem of dynamically positioning a fleet of tugs in order to mitigate the risk of oil tanker drifting accidents. In this paper, we define the 1D tug fleet optimisation problem and present a receding horizon genetic algorithm for solving it. The algorithm can be configured with a set of cost functions such that each configuration effectively constitute a unique tug fleet optimisation algorithm. To measure the performance, or merit, of such algorithms, we propose two evaluation heuristics and test them by means of a computational simulation study. Finally, we discuss our findings and some of our related work on a parallel implementation and an alternative 2D nonlinear mixed integer programming formulation of the problem.nb_NO
dc.language.isoengnb_NO
dc.publisherSpringer Verlagnb_NO
dc.relation.ispartofOperations Research and Enterprise Systems : 4th International Conference, ICORES2015 Lisbon, Portugal, January 10-12, 2015 : Revised Selected Papers
dc.titleA Simulation Study of Evaluation Heuristics for Tug Fleet Optimisation Algorithmsnb_NO
dc.typeChapternb_NO
dc.description.versionpublishedVersionnb_NO
dc.source.pagenumber165-190nb_NO
dc.identifier.doi10.1007/978-3-319-27680-9_11
dc.identifier.cristin1322569
dc.description.localcodeThis chapter will not be available due to copyright restrictions (c) 2015 by Springernb_NO
cristin.unitcode194,63,55,0
cristin.unitnameInstitutt for IKT og realfag
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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