Developing an integrated model for evaluation Risk in Supply Chain using ANN (Case Study: Iran Alloy Steel Company)

In the last few years, supply chain management becomes more important, because of the globalization of business. By increasing complexity, level of uncertainty and risk in the chain goes up. Hence supply chain risk management has become a major issue in the organization. One of the risks existing in the supply chain is risk of suppliers. This research provides model for predicting supplier risk in Iran Alloy Steel Company that is then analyzed using Artificial Neural Networks which are capable to consider non-liner interrelations among criteria. In the model using fuzzy Delphi, seven criteria have been identified. Then by using AHP-VIKOR the risk of supplier calculated and the risk of suppliers were predicted. Finally, we use sensitive analysis for identification effect of every input on output.