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

Author(s)
Vempiliyath, Thomas  
Thakur, Maitri  
Hargaden, Vincent  
Uri
http://hdl.handle.net/10197/26144
Date Issued
2021-09-22
Date Available
2024-06-04T15:35:21Z
Abstract
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.
Sponsorship
European Commission Horizon 2020
Other Sponsorship
VALUMICS project
Type of Material
Journal Article
Publisher
MDPI
Journal
Agriculture
Volume
11
Issue
10
Start Page
1
End Page
17
Copyright (Published Version)
2021 the Authors
Subjects

Farmed salmon supply ...

Discrete-event simula...

Agent-based modelling...

Hybrid simulation

Production planning

DOI
10.3390/agriculture11100907
Language
English
Status of Item
Peer reviewed
ISSN
2077-0472
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by/3.0/ie/
File(s)
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Agriculture for Open Access.pdf

Size

970.29 KB

Format

Adobe PDF

Checksum (MD5)

365cbfa8861743ba5686648f53b2ec4a

Owning collection
Mechanical & Materials Engineering Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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