An integrated T-spherical fuzzy GLDS method for evaluating resiliency in the food supply chain

Abstract

A resilient food supply chain is vital for maintaining the stability and efficiency of food distribution systems. This study introduces a novel approach that integrates a T-spherical fuzzy set with the Group Linear Distance System (GLDS) method to evaluate resiliency in the food supply chain. The T-spherical fuzzy set is utilized to handle the food supply chain’s uncertainties and vagueness in assessing resiliency factors, such as farmers, processors, wholesalers, supermarkets, and small retailers. The TSF-GLDS method is integrated with the PWA operator and using entropy measurement, the significance weights of these factors are determined and the resiliency index is calculated. The approach provides a comprehensive and reliable tool for decision-makers to assess and enhance the resiliency of food supply chains. This article verifies the constructed method’s validity and practicality through examples. The results demonstrate its ability to quantitatively measure the degree of resiliency and provide insights for optimizing food supply chain operations. To summarize, this integrated approach contributes to the better understanding and managing resiliency in food supply chains, ultimately leading to more robust and reliable systems.