Supply chain (SC) has been continuously affected by the epidemic and political situation, which has greatly impacted the SC disruption risk management. This situation evokes attention to control the SC inventory management under ripple effect. In addition, the need for supplier selection and disruption risk management can affect the SC inventory management over the planning time horizon. However, most existing works focus on inventory management, supplier selection, and disruption risk assessment separately. This work investigate an integrated inventory management, supplier selection, and disruption risk assessment under ripple effect. For the problem, a novel mixed-integer optimal control blended with dynamic Bayesian network (DBN) is formulated. The mixed-integer optimal control, proposed by Sager (2005), can portray the dynamic process consisting of continuous and discrete control variables. The DBN is applied to establish probabilistic relationships among SC participants, and to evaluate the disruption risk of the manufacturer. Two performance indexes are proposed to minimize the total cost and the disrupted probability for the manufacturer simultaneously. Then, a solution method is established to solve the problem, and an illustrative example is presented to demonstrate the proposed method.