A model-based rescheduling framework for managing abnormal supply chain events

Enterprises today have realized the importance of supply chain management to achieve operational efficiency, cut costs, and maintain quality. Uncertainties in supply, demand, transportation, market conditions, and many other factors can interrupt supply chain operations, causing significant adverse effects. These uncertainties motivate the development of decision support systems for managing disruptions in the supply chain. In this paper, we propose a model-based framework for rescheduling operations in the face of supply chain disruptions. A causal model, called the composite-operations graph, captures the cause-and-effect among all the variables in supply chain operation. Its subgraph, called scheduled-operations graph, captures the causal relationships in a schedule and is used for identifying the consequences of a disruption. Rescheduling is done by searching a rectifications-graph, which captures all possible options to overcome the disruption effects, based on a user-specified utility function. In contrast to heuristic approaches, the main advantages of the proposed model-based rescheduling method are the completeness of solution search and flexibility of the utility function. The proposed framework is illustrated using a refinery supply chain example.