We describe an application of a dynamic replanning technique in a highly dynamic and complex domain: the military aeromedical evacuation of patients to medical treatment facilities. U.S. Transportation Command (USTRANSCOM) is the DoD agency responsible for evacuating patients during wartime and peace. Doctrinally, patients requiring extended treatment must be evacuated by air to a suitable Medical Treatment Facility (MTF). The Persian Gulf war was the first significant armed conflict in which this concept has been put to a serious test. The results were far from satisfactory -- about 60% of the patients ended up at the wrong destinations. In early 1993, the Department of Defense tasked USTRANSCOM to consolidate the command and control of medical regulation and aeromedical evacuation operations. The ensuing analysis led to TRAC2ES (TRANSCOM Regulating and Command and Control Evacuation System), a decision support system for planning and scheduling medical evacuation operations. Probably the most challenging aspect of the problem has to do with the dynamics of a domain in which requirements and constraints continuously change over time. Continuous dynamic replanning is a key capability of TRAC2ES. This paper describes the application and the AI approach we took in providing this capability.