Ranking Supply Chain Disruptions Using Mix Method, Fuzzy Dematel & Meta Heuristic Algorithms

Among the types of supply chain risks disruptions are risks that resulting from natural disasters, sanctions, transportation problems and equipment failure.
These risks can seriously disrupt the flow of materials, information and cash flow. This study proposes a hybrid model for managing, evaluating and rating disorders. In this research, by presenting a mathematical model with disruption parameter, supply chain disruption risk assessment is investigated. Initially, the relationships between the disturbances are formulated by fuzzy DEMATEL technique, and the DEMATEL output as a weighted parameter, and then the model is solved using meta-heuristic algorithms, genetic and local search methods. Finally, the disruptions are evaluated and ranked based on the costs incurred in the chain, and then the number of appropriate suppliers for each disruption is determined.