Integrating analytic network process and multi-objective decision making for mathematical modeling the resilient supply chain of Mobarakeh Steel Company

Supply chains are subject to numerous changes that increase the complexity and vulnerability to disturbances. Therefore, for survival organizations and their supply chains must be elastic. In other words organizations must develop the ability to respond to an unforeseen disorder and after enduring the disorder, have a quick return to their core position or move to a new and better place with more competitive advantage. One of the approaches to dealing with these disorders is to identify and predict disturbing supply chain risks and provide solutions to reduce these disruptions. Considering this approach, in this research the identification of disturbing risks in Mobarakeh Steel Company's supply chain and then reducing their potential effects for the next four periods has been considered. According to the experts of the company the graphite electrode is the most important and strategically important material. Therefore the risks associated with supplying this substance were introduced as supply chain disruptive risks and weighed them using ANP method. According to the results it was found that the most important risk for the company's experts is the risk of non-flexibility of suppliers of graphite electrode with a weight of 0.5436. Other risks, the risk of long delivery orders, the risk of low quality and the risk of price increases, have the weights of 0.1911, 0.1716 and 0.0937, respectively. The weights of these risks was considered as the coefficients of four objective functions in which each of them intended to minimize one of the identified risks. Then due to the importance of the company's risks and using the absolute priority method the company's optimization model was solved and it was determined how much graphite electrode should be purchased from each supplier in each period.