A Robust Neutrosophic Model for Risk Management in Livestock Supply Chains: A Case Study Towards Sustainable Practices

Abstract

This study proposed a decision machining methodology to identify and evaluate the risks based on the 
livestock supply chain (LSC). The risks related to LSC are identified and collected by the opinion of the 
experts and decision-makers. We collected 11 LSC criteria and nine alternatives. We proposed an 
uncertainty framework to deal with uncertainty and vague information in the evaluation process. We used 
the type-2 neutrosophic set (T2NSs) to deal with vague data. The T2NSs were proposed under multi
objective optimization based on simple ratio analysis (MOOSRA) to rank the alternatives. We identified 
nine strategies to reduce risks in LSC. The results show that operational risks have the highest weights. We 
applied sensitivity analysis to show the different ranks of alternatives under different criteria weights. The 
results show the proposed method is stable under different weights. Finally, we conducted a comparative 
analysis between other methods to show the robustness of the proposed method. 

DOI: 10.5281/zenodo.14241621