Sustainable Food Supply Chain Screening and Relationship Analysis with Unknown Criteria Weight Information

Abstract

Sustainable food supply chain management (SFSC) can control food loss and waste by reduc­ing resource consumption and environmental pollution, thereby ensuring sustainable food consumption and production patterns. Scholars have investigated specific aspects or links in SFSC but rarely studied the sustainability evaluation and selection of a whole supply chain to provide management suggestions under uncertain decision-making environments. This paper presents a comprehensive multiple criteria decision-making method called the SMAA-ORESTE method for SFSC selection. To reduce experts’ efforts, the holistic acceptability index in the SMAA-2 method is used to screen inferior SFSCs from a large num­ber of alternatives. Then, the ORESTE method is combined with the SMAA method to evaluate SFSCs under uncertain information. The ORESTE method can specifically analyze the relationship between al­ternatives, and the SMAA method can analyze alternatives with unknown criteria weights by Monte Carlo simulation. The proposed method ensures the robustness and credibility of obtained ranking results. An illustrative example validates the applicability and robustness of the proposed method in selecting SFSCs with unknown criteria weights.