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A robust location-inventory model for food supply chains operating under disruptions with ripple effects

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  • Seyed Mohammad Gholami-Zanjani
  • Mohammad Saeed Jabalameli
  • Walid Klibi
  • Mir Saman Pishvaee

Abstract

Given the inevitable globalisation in the food sector and the specific security challenges this industry faces, designing food supply chains has become a substantial topic for academics and practitioners. The integration of food product-specific characteristics and potential disruptions has continuously gained importance because it better reflects real-world problems and responds to a crucial need for resilience, robustness, and competitiveness. In this article, a generic two-stage mixed-integer mathematical model is developed to integrate key features of location-allocation and inventory-replenishment decisions. Then, food-specific disruptions with ripple effects are incorporated through plausible scenarios. For such a setting, three resiliency strategies – namely, readiness, flexibility, and responsiveness – are used to deal with uncertainties. Based on extensive numerical experiments, the solutions obtained highlight behaviour of different design models to hedge against ripple effects as well as the importance of incorporating food-specific assumptions and risk aversion attitudes.

Suggested Citation

  • Seyed Mohammad Gholami-Zanjani & Mohammad Saeed Jabalameli & Walid Klibi & Mir Saman Pishvaee, 2021. "A robust location-inventory model for food supply chains operating under disruptions with ripple effects," International Journal of Production Research, Taylor & Francis Journals, vol. 59(1), pages 301-324, January.
    • Handle: RePEc:taf:tprsxx:v:59:y:2021:i:1:p:301-324
    DOI: 10.1080/00207543.2020.1834159
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    Cited by:

    1. Liu, Ming & Ding, Yueyu & Chu, Feng & Dolgui, Alexandre & Zheng, Feifeng, 2024. "Robust actions for improving supply chain resilience and viability," Omega, Elsevier, vol. 123(C).
    2. Kabadurmus, Ozgur & Kayikci, Yaşanur & Demir, Sercan & Koc, Basar, 2023. "A data-driven decision support system with smart packaging in grocery store supply chains during outbreaks," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    3. Alam, Md Fahim Bin & Tushar, Saifur Rahman & Ahmed, Tazim & Karmaker, Chitra Lekha & Bari, A.B.M. Mainul & de Jesus Pacheco, Diego Augusto & Nayyar, Anand & Islam, Abu Reza Md Towfiqul, 2024. "Analysis of the enablers to deal with the ripple effect in food grain supply chains under disruption: Implications for food security and sustainability," International Journal of Production Economics, Elsevier, vol. 270(C).
    4. Jahani, Hamed & Abbasi, Babak & Sheu, Jiuh-Biing & Klibi, Walid, 2024. "Supply chain network design with financial considerations: A comprehensive review," European Journal of Operational Research, Elsevier, vol. 312(3), pages 799-839.
    5. Liu, Ming & Liu, Zhongzheng & Chu, Feng & Dolgui, Alexandre & Chu, Chengbin & Zheng, Feifeng, 2022. "An optimization approach for multi-echelon supply chain viability with disruption risk minimization," Omega, Elsevier, vol. 112(C).
    6. Sawik, Tadeusz, 2022. "Stochastic optimization of supply chain resilience under ripple effect: A COVID-19 pandemic related study," Omega, Elsevier, vol. 109(C).
    7. Germán Herrera Vidal & Camilo Molina Guerrero, 2024. "Deterministic ınventory models with non-perishable product: a comparative study," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 15(6), pages 2500-2517, June.
    8. Liu, Ming & Lin, Tao & Chu, Feng & Ding, Yueyu & Zheng, Feifeng & Chu, Chengbin, 2023. "Bi-objective optimization for supply chain ripple effect management under disruption risks with supplier actions," International Journal of Production Economics, Elsevier, vol. 265(C).

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