A Fuzzy Multi-Criteria Optimization Framework for Resilient Supply Chain Design Under Demand, Disruption, and Sustainability Uncertainty

Abstract

A fuzzy multi-criteria optimization model for resilient supply chain design for demand, disruption and sustainability uncertainty. The data set consisted of 1,000 supply chain transactions, with a set of operational, supplier, disruption, transportation, economic, and energy-related indicators applied. The normalization, fuzzy representation, weighting, aggregation and ranking procedures were applied to incorporate the following decision criteria: demand variability, disruption exposure, delivery delay, supplier reliability, supply risk, and energy consumption. Results showed that there was a great deal of variation in the demand and that supply-risk exposure had a considerable impact on the operations, including delivery delays. Based on the multi-criteria evaluation, Supplier S12 was identified as the best alternative with a baseline composite score of 0.871. Its robustness was also shown in a scenario analysis where it continued to be the top performer in the demand-priority, severe-disruption, sustainability-priority and combined-uncertainty scenarios. The secondary supplier ranking was different for each scenario, reflecting sensitivity to the shifting managerial priorities. Under the proposed framework, there is a structured way to balance the economic efficiency, disruption-resilience, supplier reliability and sustainability in supply chain decisions where uncertainty exists.