Development of a hybrid simulation framework for the production planning process in the atlantic salmon supply chain

The farmed salmon supply chain has a highly complex and integrated structure, where activities occur both in the sea and on land. Due to this complexity, the supply chain needs appropriate decision-support tools to aid the production planning process, which capture the material flows, information fl...

Full description

Bibliographic Details
Published in:Agriculture
Main Authors: Vempiliyath, Thomas, Thakur, Maitri, Hargaden, Vincent
Format: Article in Journal/Newspaper
Language:English
Published: MDPI 2021
Subjects:
Online Access:https://hdl.handle.net/11250/3026605
https://doi.org/10.3390/agriculture11100907
id ftsintef:oai:sintef.brage.unit.no:11250/3026605
record_format openpolar
spelling ftsintef:oai:sintef.brage.unit.no:11250/3026605 2023-05-15T15:31:09+02:00 Development of a hybrid simulation framework for the production planning process in the atlantic salmon supply chain Vempiliyath, Thomas Thakur, Maitri Hargaden, Vincent 2021 application/pdf https://hdl.handle.net/11250/3026605 https://doi.org/10.3390/agriculture11100907 eng eng MDPI Agriculture. 2021, 11 (10), 1-17. urn:issn:2077-0472 https://hdl.handle.net/11250/3026605 https://doi.org/10.3390/agriculture11100907 cristin:1997414 Navngivelse 4.0 Internasjonal http://creativecommons.org/licenses/by/4.0/deed.no Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). CC-BY 17 11 Agriculture 10 hybrid simulation production planning discrete-event simulation (DES) agent-based modelling (ABM) farmed salmon supply chain Peer reviewed Journal article 2021 ftsintef https://doi.org/10.3390/agriculture11100907 2022-10-19T22:42:51Z The farmed salmon supply chain has a highly complex and integrated structure, where activities occur both in the sea and on land. Due to this complexity, the supply chain needs appropriate decision-support tools to aid the production planning process, which capture the material flows, information flows and behaviours of the decision makers in the chain. This paper proposes a hybrid simulation framework for production planning using the case of the Norwegian Atlantic salmon supply chain. This hybrid simulation comprises agent-based modelling (ABM) to capture the autonomous and interacting decision making behaviour of the supply chain actors, while discrete-event simulation (DES) is employed to model the various production processes within the chain. The simulation is implemented using AnyLogic™ version 8.0 simulation software, using a case study from the Norwegian farmed salmon sector. The proposed modelling framework provides a deeper understanding of the activities in the salmon supply chain, thereby enabling improved decision making. publishedVersion Article in Journal/Newspaper Atlantic salmon SINTEF Open (Brage) Agriculture 11 10 907
institution Open Polar
collection SINTEF Open (Brage)
op_collection_id ftsintef
language English
topic hybrid simulation
production planning
discrete-event simulation (DES)
agent-based modelling (ABM)
farmed salmon supply chain
spellingShingle hybrid simulation
production planning
discrete-event simulation (DES)
agent-based modelling (ABM)
farmed salmon supply chain
Vempiliyath, Thomas
Thakur, Maitri
Hargaden, Vincent
Development of a hybrid simulation framework for the production planning process in the atlantic salmon supply chain
topic_facet hybrid simulation
production planning
discrete-event simulation (DES)
agent-based modelling (ABM)
farmed salmon supply chain
description The farmed salmon supply chain has a highly complex and integrated structure, where activities occur both in the sea and on land. Due to this complexity, the supply chain needs appropriate decision-support tools to aid the production planning process, which capture the material flows, information flows and behaviours of the decision makers in the chain. This paper proposes a hybrid simulation framework for production planning using the case of the Norwegian Atlantic salmon supply chain. This hybrid simulation comprises agent-based modelling (ABM) to capture the autonomous and interacting decision making behaviour of the supply chain actors, while discrete-event simulation (DES) is employed to model the various production processes within the chain. The simulation is implemented using AnyLogic™ version 8.0 simulation software, using a case study from the Norwegian farmed salmon sector. The proposed modelling framework provides a deeper understanding of the activities in the salmon supply chain, thereby enabling improved decision making. publishedVersion
format Article in Journal/Newspaper
author Vempiliyath, Thomas
Thakur, Maitri
Hargaden, Vincent
author_facet Vempiliyath, Thomas
Thakur, Maitri
Hargaden, Vincent
author_sort Vempiliyath, Thomas
title Development of a hybrid simulation framework for the production planning process in the atlantic salmon supply chain
title_short Development of a hybrid simulation framework for the production planning process in the atlantic salmon supply chain
title_full Development of a hybrid simulation framework for the production planning process in the atlantic salmon supply chain
title_fullStr Development of a hybrid simulation framework for the production planning process in the atlantic salmon supply chain
title_full_unstemmed Development of a hybrid simulation framework for the production planning process in the atlantic salmon supply chain
title_sort development of a hybrid simulation framework for the production planning process in the atlantic salmon supply chain
publisher MDPI
publishDate 2021
url https://hdl.handle.net/11250/3026605
https://doi.org/10.3390/agriculture11100907
genre Atlantic salmon
genre_facet Atlantic salmon
op_source 17
11
Agriculture
10
op_relation Agriculture. 2021, 11 (10), 1-17.
urn:issn:2077-0472
https://hdl.handle.net/11250/3026605
https://doi.org/10.3390/agriculture11100907
cristin:1997414
op_rights Navngivelse 4.0 Internasjonal
http://creativecommons.org/licenses/by/4.0/deed.no
Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).
op_rightsnorm CC-BY
op_doi https://doi.org/10.3390/agriculture11100907
container_title Agriculture
container_volume 11
container_issue 10
container_start_page 907
_version_ 1766361640221016064