Integrating time and cost in dynamic optimization of supply chain recovery

The occurrence of disruptions has undeniable impacts on supply chain (SC) performance and severely affects its costs and revenues. SC resilience (SCR) reduces the impacts of these disruptions. Among the issues in the SCR, although the recovery of the SC after the disruption is of vital importance, it has not been considered as it should be. To fill this gap, this paper enumerates some important issues in SC recovery planning and proposes a dynamic model for it. One of the features of the proposed model is to consider the recovery time and cost in order to achieve the pre-disruption SC performance. Then, we demonstrate the application of this model in the recovery of a two-echelon poultry SC. Since the developed model is a nonlinear dynamic model, we use the direct collocation method to solve it. The outputs of the sensitivity analysis show that changes in many parameters result in significant changes in model variables. Based on the results, it can be said that the development of appropriate models for recovery plays an important role in the analysis of possible alternatives for SC recovery and can help SC managers to deal with disruptions by comparing alternative recovery options.