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dc.contributor.authorBrevik, Elisabeth
dc.contributor.authorLauen, Anna Ødegaard
dc.contributor.authorRolke, Maria Cathrine Berg
dc.contributor.authorFagerholt, Kjetil
dc.contributor.authorHansen, Jone Reinlund
dc.date.accessioned2020-08-25T07:54:11Z
dc.date.available2020-08-25T07:54:11Z
dc.date.created2020-01-01T17:17:11Z
dc.date.issued2020
dc.identifier.citationInternational Journal of Production Research. 2020, 58 (17), 5218-5237en_US
dc.identifier.issn0020-7543
dc.identifier.urihttps://hdl.handle.net/11250/2673789
dc.description.abstractIn this paper, we propose a mixed integer programming (MIP) model for the Chicken Flock Sizing, Allocation and Scheduling Problem (CFSASP), which is an important planning problem in the broiler production supply chain. To solve the CFSASP efficiently, two variants of rolling horizon heuristics (RHHs) have been developed and applied on the case of a Norwegian broiler production company. Computational results show that the RHHs successfully obtain high-quality solutions within a reasonable time. The value of optimisation is verified through comparison with the case company's plans, where the solutions from optimisation outperforms the current solutions. Sensitivity analyses are also conducted to provide managerial insights regarding certain strategic decisions, such as how many and which days to use for hatching of chickens. Due to the promising results, the case company is now implementing an optimisation-based decision support system based on the MIP model and solution methods shown in this paper.en_US
dc.language.isoengen_US
dc.publisherTaylor & Francisen_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.no*
dc.titleOptimisation of the broiler production supply chainen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.source.pagenumber5218-5237en_US
dc.source.volume58en_US
dc.source.journalInternational Journal of Production Researchen_US
dc.source.issue17en_US
dc.identifier.doi10.1080/00207543.2020.1713415
dc.identifier.cristin1764726
dc.description.localcode© 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.en_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2


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Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal
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