dc.contributor.author | Brevik, Elisabeth | |
dc.contributor.author | Lauen, Anna Ødegaard | |
dc.contributor.author | Rolke, Maria Cathrine Berg | |
dc.contributor.author | Fagerholt, Kjetil | |
dc.contributor.author | Hansen, Jone Reinlund | |
dc.date.accessioned | 2020-08-25T07:54:11Z | |
dc.date.available | 2020-08-25T07:54:11Z | |
dc.date.created | 2020-01-01T17:17:11Z | |
dc.date.issued | 2020 | |
dc.identifier.citation | International Journal of Production Research. 2020, 58 (17), 5218-5237 | en_US |
dc.identifier.issn | 0020-7543 | |
dc.identifier.uri | https://hdl.handle.net/11250/2673789 | |
dc.description.abstract | In 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.iso | eng | en_US |
dc.publisher | Taylor & Francis | en_US |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/deed.no | * |
dc.title | Optimisation of the broiler production supply chain | en_US |
dc.type | Peer reviewed | en_US |
dc.type | Journal article | en_US |
dc.description.version | publishedVersion | en_US |
dc.source.pagenumber | 5218-5237 | en_US |
dc.source.volume | 58 | en_US |
dc.source.journal | International Journal of Production Research | en_US |
dc.source.issue | 17 | en_US |
dc.identifier.doi | 10.1080/00207543.2020.1713415 | |
dc.identifier.cristin | 1764726 | |
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.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 2 | |