An optimization algorithm can be implemented to allocate the optimal quantity of inventory to each node, considering probability of disruption, expected demand, and travel time to the possible emergency location(s). Cost measures can also be included (e.g., travel cost and inventory cost) to track the overall fulfillment cost. Additional constraints can be added to include an the expiration date of some critical products (e.g., medicines, blood inventory).
The generalizability of this approach allows for implementation and replication in different contexts and geographies.