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Conceptual framework for designing agri-food supply chains under uncertainty by mathematical programming models

Author

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  • Ana Esteso
  • M.M.E. Alemany
  • Angel Ortiz

Abstract

Agri-food sector performance strongly impacts global economy, which means that developing optimisation models to support the decision-making process in agri-food supply chains (AFSC) is necessary. These models should contemplate AFSC’s inherent characteristics and sources of uncertainty to provide applicable and accurate solutions. To the best of our knowledge, there are no conceptual frameworks available to design AFSC through mathematical programming modelling while considering their inherent characteristics and sources of uncertainty, nor any there literature reviews that address such characteristics and uncertainty sources in existing AFSC design models. This paper aims to fill these gaps in the literature by proposing such a conceptual framework and state of the art. The framework can be used as a guide tool for both developing and analysing models based on mathematical programming to design AFSC. The implementation of the framework into the state of the art validates its. Finally, some literature gaps and future research lines were identified.

Suggested Citation

  • Ana Esteso & M.M.E. Alemany & Angel Ortiz, 2018. "Conceptual framework for designing agri-food supply chains under uncertainty by mathematical programming models," International Journal of Production Research, Taylor & Francis Journals, vol. 56(13), pages 4418-4446, July.
    • Handle: RePEc:taf:tprsxx:v:56:y:2018:i:13:p:4418-4446
    DOI: 10.1080/00207543.2018.1447706
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    Citations

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    Cited by:

    1. G. Denisse Chamochumbi D. & Massimo Ciambotti & Federica Palazzi & Francesca Sgr?, 2022. "The digital transformation process in the agri-food sector: A case study," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2022(2 Suppl.), pages 43-70.
    2. Tuğçe Taşkıner & Bilge Bilgen, 2021. "Optimization Models for Harvest and Production Planning in Agri-Food Supply Chain: A Systematic Review," Logistics, MDPI, vol. 5(3), pages 1-27, August.
    3. D. G. Mogale & Sri Krishna Kumar & Manoj Kumar Tiwari, 2020. "Green food supply chain design considering risk and post-harvest losses: a case study," Annals of Operations Research, Springer, vol. 295(1), pages 257-284, December.
    4. Gholami-Zanjani, Seyed Mohammad & Klibi, Walid & Jabalameli, Mohammad Saeed & Pishvaee, Mir Saman, 2021. "The design of resilient food supply chain networks prone to epidemic disruptions," International Journal of Production Economics, Elsevier, vol. 233(C).
    5. Barbara Iannone & Giulia Caruso, 2023. "“Sustainab-lization”: Sustainability and Digitalization as a Strategy for Resilience in the Coffee Sector," Sustainability, MDPI, vol. 15(6), pages 1-32, March.
    6. De, Arijit & Gorton, Matthew & Hubbard, Carmen & Aditjandra, Paulus, 2022. "Optimization model for sustainable food supply chains: An application to Norwegian salmon," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
    7. Nouira, Imen & Hammami, Ramzi & Fernandez Arias, Alina & Gondran, Natacha & Frein, Yannick, 2022. "Olive oil supply chain design with organic and conventional market segments and consumers’ preference to local products," International Journal of Production Economics, Elsevier, vol. 247(C).
    8. Ge, Houtian & Goetz, Stephan J. & Cleary, Rebecca & Yi, Jing & Gómez, Miguel I., 2022. "Facility locations in the fresh produce supply chain: An integration of optimization and empirical methods," International Journal of Production Economics, Elsevier, vol. 249(C).

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