Multi-agent architecture for waste minimisation in beef supply chain

被引:8
作者
Nguyen, Ai Ha Thi [1 ]
Singh, Akshit [2 ]
Kumari, Sushma [3 ]
Choudhary, Sonal [4 ]
机构
[1] Nong Lam Univ, Fac Agron, Ho Chih Minh, Vietnam
[2] Univ Liverpool Management Sch, Liverpool, Merseyside, England
[3] Univ Hull, Hull Univ Business Sch, Kingston Upon Hull, N Humberside, England
[4] Univ Sheffield, Sheffield Univ Management Sch, Sheffield, S Yorkshire, England
关键词
Beef supply chain; waste minimisation; multi-agent system (MAS); MANAGEMENT; QUALITY; CATTLE; INDUSTRY; LOSSES; IMPACT;
D O I
10.1080/09537287.2021.1979679
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
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.
引用
收藏
页码:1082 / 1096
页数:15
相关论文
共 55 条
  • [1] Losses, inefficiencies and waste in the global food system
    Alexander, Peter
    Brown, Calum
    Arneth, Almut
    Finnigan, John
    Moran, Dominic
    Rounsevell, Mark D. A.
    [J]. AGRICULTURAL SYSTEMS, 2017, 153 : 190 - 200
  • [2] [Anonymous], 2003, International Food and Agribusiness Management Review
  • [3] [Anonymous], Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change
  • [4] [Anonymous], 2019, Food Loss and Food Waste
  • [5] Temperature management for the quality assurance of a perishable food supply chain
    Aung, Myo Min
    Chang, Yoon Seok
    [J]. FOOD CONTROL, 2014, 40 : 198 - 207
  • [6] Supply chain risk management and artificial intelligence: state of the art and future research directions
    Baryannis, George
    Validi, Sahar
    Dani, Samir
    Antoniou, Grigoris
    [J]. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2019, 57 (07) : 2179 - 2202
  • [7] Environmental Impacts and Hotspots of Food Losses: Value Chain Analysis of Swiss Food Consumption
    Beretta, Claudio
    Stucki, Matthias
    Hellweg, Stefanie
    [J]. ENVIRONMENTAL SCIENCE & TECHNOLOGY, 2017, 51 (19) : 11165 - 11173
  • [8] Boucher Dug., 2012, Grade A Choice? Solutions for Deforestation-Free Meat
  • [9] A simulation study with quantity flexibility in a supply chain subjected to uncertainties
    Chan, FTS
    Chan, HK
    [J]. INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING, 2006, 19 (02) : 148 - 160
  • [10] Identifying inventory problems in the aerospace industry using the theory of constraints
    Chou, Ying-Chyi
    Lu, Ching-Hua
    Tang, Ya-Yun
    [J]. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2012, 50 (16) : 4686 - 4698