Nowadays, it is necessary to paying attention to the opportunities and threats in the field of industry and trade, and evaluate the ability of industries and companies in dealing with uncertainties and existing risks, and it is very important to manage supply chain risk. The main purpose of this study is to be careful against risky suppliers and reducing the injury rate in the event of a disruption. Therefore, in this regard, a multi-stage mixed integer programming model with a proactive approach has been used; that in the first stage, the model reports the amount of supply from suppliers without considering the risk criterion, and at the same time, it seeks to optimal state of minimization the supply chain costs (including purchase cost, shipping, maintenance, supplier selection and return goods). In the second stage, after the suppliers which supplying the parts, have been identified, the model seeks to minimize the identified risks of suppliers under different scenarios. In the third stage, the model tries to achieve an optimal state of supplying the parts from less risky suppliers. In the continuation of this study, an integrated multi-objective programming model has been designed, which will be solved by the epsilon constraint method, and the best output will be reported from the Pareto’s optimal set of answers; Finally the results of the model will be compared in two multi-stage and integrated multi-objective modes and the correctness of the performance is confirmed.