A new dynamic optimisation model for operational supply chain recovery

This paper focuses on the problem of dynamic supply chain (SC) recovery. We consider effectiveness and efficiency of various reactive measures to recover the SC with the minimum cost at the operational level. For this purpose, a new general model based on bounded optimal control theory is developed to determine the type, the extent, and the timing of reactive measures. We demonstrate its application using an example of a two-echelon poultry SC. The intention of the proposed model is to optimise both the recovery and its costs simultaneously. The developed model is solved exactly using the Pontryagin's maximum principle. We performed a set of sensitivity analyses to illustrate the model's behaviour. The results obtained from applying the dynamic recovery model in the case study show that the proposed model can help SC managers to deal with disruptions by comparing alternative recovery options, based on two important criteria of the time and cost of SC's recovery. The findings of this research advocate the consideration of dynamic SC characteristics and the need for simultaneous attention to the effectiveness and efficiency of reactive measures in recovery planning.

Automated summary

This paper introduces a new general model based on bounded optimal control theory to determine the type, extent, and timing of reactive measures for supply chain recovery at the operational level. An example of a two-echelon poultry SC is used to demonstrate its application. The results show that the proposed model can help SC managers compare alternative recovery options based on time and cost criteria.