سید رضا هاشمی - MA Student of Industrial Engineering, Babol Noshirvani University of Technology, Babol, Iran
عبدالله آراسته - Assistant Professor, Department of Industrial Engineering, Babol Noshirvani University of Technology, Babol, Iran
محمدمهدی پایدار - Associate Professor, Department of Industrial Engineering, Babol Noshirvani University of Technology, Babol, Iran

This study proposes a multi-stage supply chain model with direct and reverse flows of goods to assess the effects of risk on the profit of a supply chain network and the realization of demand. The studied network aims to maximize profit, minimize unmet demand, reduce delivery time, alleviate disruption risks in facilities and transportation, and decrease supply chain visibility. We created a system for quantifying the disruption risk ratings of supply chain components. To help the company better understand its suppliers, address essential network components, and prioritize risk management initiatives, the evaluation may be useful. For our supply chain optimization models, we rely on the predicted disruption risk ratings as a basis. Goal programming is used to solve the multi-criteria model. The resiliency of the supply chain network is shown numerically. In order to build the model, the designer had to make strategic judgments. Risk mitigation methods such as extra inventory and backup suppliers are adopted to increase the supply chain network’s resiliency. Short-term disruptions may be mitigated by stockpiling additional raw materials to avoid component shortages. A cost-benefit analysis shows that every risk reduction strategy is worthwhile.

Multi-objective optimization, Goal Programming, Lexicography, Weighting method