Implications of unmet demand within the context of supply chain restoration

Abstract

Upon creating this new supply chain restoration model and implementing it in AMPL, using CPLEX 11.0 as the integer programming solver, we offer some policy insights on supply chain restoration that reflect the results gathered in our analysis, including the fact that contracts for back-up facilities are only purchased when the supply chain system intends on exhausting that back-up facility for its total supply capacity. When a supply chain system uses back-up facilities to minimize customer loss, most of the back-up supply that is produced is shipped to the facilities which can then best ship units of supply least expensively to the customers that the model aims to avoid losing. Additionally, when the supply chain system is able to replace lost customers quickly, it is more willing to lose those customers in the system as opposed to carrying out restoration efforts to satisfy their demands. Lastly, especially as it applies to selecting restoration strategies following a large disruption, tradeoffs are made in the attempt to maintain the loyalty of a select group of customers in the system. This typically results in the loss of a larger number of other customers in the system that have lower demand and customer-loss costs associated with them.

In this thesis, a new supply chain restoration model is created that aims to model the impact that yielded unmet demand has on customer loyalty in supply chain systems during periods of restoration. When an extreme event such as an earthquake or a hurricane disrupts a supply chain system, diminishing the amount of supply that facilities are able to produce in that supply chain system, certain restoration strategies can be carried out as a means of restoring capacity and ultimately maintaining customer loyalty. Our model incorporates a back-up-facility-purchasing strategy that allows for disrupted facilities to receive temporary supply that can be used for meeting customer demand.