The Medication Distribution Problem

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In a case of a bioterrorism attack, public health officials need to be prepared so the country, state, and counties are able to respond to any threat. The medication distribution problem specifically focuses on the state and local government levels of medication distribution to the points of dispensing (PODs). If health officials decide that mass dispensing of medication is needed, the PODs will be prepared as locations to administer the medication to the public. The state will then request medication from the federal government to be delivered to a state depot, where the medications will be stored until it is delivered to the PODs. The federal government will make multiple shipments, or waves, of medication to the depot. Likewise multiple shipments of medication will be made from the depot to the PODs.

The health officials have two strategic alternatives in order to ensure timely deliveries are made to the PODs.

  1. Using an LDC. A county may choose to operate a local distribution center (LDC) which receives medications from the depot. The LDC then distributes the materials to the PODs within the LDC’s jurisdiction.
  2. Not using an LDC. The second strategic alternative for the counties is to forgo having an LDC so that the medication will be delivered from the depot directly to the PODs.

Variable aspects of the problem include the routes used by the trucks to deliver the medication, the travel time of the trucks (travel time to the PODs and time to finish a route), time to load and unload the trucks, and the demand of medication per each POD. The best solution is determined by maximizing the probability that the PODs open on-time and do not run out of medication during operation.

Assuming truck routes have already been determined, this paper addresses the scheduling aspect of mass medication distribution. The focus will be optimizing the schedules—deciding when a POD will receive a delivery and the amount of medication sent to the PODs during each delivery.


This report is the final project of a student in ISR's 2008 Research Experiences for Undergraduates program.