Disruption-driven supply chain (re)-planning and performance impact assessment with consideration of pro-active and recovery policies

Supply chain planning models under disruptions are extensively studied in literature. In this paper, we consider a multi-stage supply chain (re)planning problem. We propose a new approach with an explicit connection of performance impact assessment and supply chain plan reconfiguration issues with consideration of the duration of disruptions and the costs of recovery. This approach is based on a hybrid model containing elements of system dynamics and linear programming. The supply chain structure dynamics and recovery is considered in the dynamic model while a linear programming model is used for flow balance. We transit from the classical linear programming model to maximal flow problem by excluding demand constraints. The results have several major implications. First, a method to compare different actions for supply chain resilience regarding the performance impact is suggested. Second, since the commodity flows are described in continuous time, the disruption recovery time can be described more easily. Third, service level and sales volumes can be included as resilience indicators into the performance analysis consideration. Subsequently, through numerical computations, we obtain additional managerial insights. As extensions, we study the impact of different changes in supply chain design and plans on supply chain performances. Based on these results, diverse execution scenarios can be considered and suggestions on re-planning in the case of disruptions regarding the trade-off “efficiency vs. resilience” can be developed.