Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/36355
Appears in Collections:Management, Work and Organisation Journal Articles
Peer Review Status: Refereed
Title: Multi-agent architecture for waste minimisation in beef supply chain
Author(s): Nguyen, Ai Ha Thi
Singh, Akshit
Kumari, Sushma
Choudhary, Sonal
Contact Email: akshit.singh@stir.ac.uk
Keywords: Beef Supply chain
waste minimisation
mulit-agent system (MAS)
Issue Date: 2023
Date Deposited: 9-Oct-2024
Citation: Nguyen AHT, Singh A, Kumari S & Choudhary S (2023) Multi-agent architecture for waste minimisation in beef supply chain. <i>Production Planning & Control</i>, 34 (11), pp. 1082-1096. https://doi.org/10.1080/09537287.2021.1979679
Abstract: Food waste is an alarming issue pertaining to the rising global hunger, huge environmental footprint, and high monetary value. In developing and developed nations, it occurs primarily due to inefficiencies upstream and downstream of the supply chain respectively. A common factor in both developed and developing nations is product flow within the supply chain from farms to retailers. This study aims to identify the root causes of waste generated across the product flow of the beef supply chain from farm to retailer. A workshop involving twenty practitioners of the beef industry was conducted and the collected information was transcribed and coded to generate a current reality tree, which assisted in identifying root causes of waste in the entire beef supply chain. A multi-agent architecture framework spanning the entire beef supply chain from farm to retailer is proposed, which is composed of autonomous agents capable of bringing all segments of the beef industry on a single platform and collaboratively assist them in mitigating root causes of waste. The proposed framework will aid the practitioners in the beef industry to reduce waste, improve their operational efficiency thereby raising food security, economic development whilst curbing their carbon footprint.
DOI Link: 10.1080/09537287.2021.1979679
Rights: © 2021 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 License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Licence URL(s): http://creativecommons.org/licenses/by/4.0/

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