A Fermatean Fuzzy ORESTE Method For Evaluating The Resilience of the Food Supply Chain

Authors

DOI:

https://doi.org/10.31181/jopi2120249

Keywords:

Food Supply Chain, Resilience, Fermatean Fuzzy Set, ORESTE method

Abstract

To study the resilience and driving factors of key players in the food supply chain, this paper applies a decision model based on the Fermatean fuzzy set and improved ORESTE method. Firstly, based on the existing research on food supply chain resilience, the risk influencing factors affecting food supply chain resilience is established through a literature review. Secondly, Fermatean fuzzy sets are used to express and integrate uncertain information, calculate the membership and non-membership degrees of the factors affecting the resilience risk of the food supply chain, and then calculate the score function to obtain the weight of the influencing factors and the risk weight of alternatives. Finally, the improved ORESTE method is used to rank key players, thereby identifying key players in the food supply chain that affect resilience. The results show that transportation and logistics failures, government regulation, and diseases are the three important risk factors with the highest weight coefficient, while water system failure is the least important risk factor. Among the key players, farmers and food processors are considered the most vulnerable key players in the food supply chain, while the most resilient key players are supermarkets and food wholesalers. 

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Author Biographies

  • Yi Wang, School of Economics and Management, Anhui Normal University, Wuhu 241000, China

    .

  • Xiao Han, School of Economics and Management, Anhui Normal University, Wuhu 241000, China

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  • Weizhong Wang, School of Economics and Management, Anhui Normal University, Wuhu 241000, China

    .

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Published

2024-01-12

Issue

Vol. 2 No. 1 (2024): Journal of Operations Intelligence

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Articles

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How to Cite

Wang, Y., Han, X., & Wang, W. . (2024). A Fermatean Fuzzy ORESTE Method For Evaluating The Resilience of the Food Supply Chain. Journal of Operations Intelligence, 2(1), 78-94. https://doi.org/10.31181/jopi2120249