An Air Mission Planning Algorithm Using Decision Analysis and Mixed Integer Programming

Brian J. Griggs, Gregory S. Parnell and Lee J. Lehmkuhl
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Brian J. Griggs: The Pentagon, Washington, DC
Gregory S. Parnell: Virginia Commonwealth University, Richmond, Virginia
Lee J. Lehmkuhl: Air Force Institute of Technology, Wright-Patterson Air Force Base, Ohio

Operations Research, 1997, vol. 45, issue 5, 662-676

Abstract: This paper describes the development of an air mission planning algorithm for the Joint Stochastic Warfare Analysis Research (JSTOCHWAR). The overall problem scope was to develop an algorithm to handle major factors bearing on the combat mission planning problem while providing hook-ups for the JSTOCHWAR architecture. Other aspects of the problem included finding the appropriate level of detail, developing a fast solving technique, and attempting to use existing data. The problem was handled by using some ideas from existing aircraft allocation algorithms and by adding some new techniques.The proposed air mission planning algorithm supplies the optimum degree of force for campaign objectives by using a mixed integer program (MIP) to allocate the optimum number and type of aircraft and munitions against each target. The MIP takes advantage of the force multiplying effects of mass and mutual support through its use of strike packages with air defense suppression and air-to-air escort aircraft. Additionally, a decision tree algorithm determines the best plan in light of the uncertainties of weather and weather forecasts.This air mission planning algorithm omits many of the details in the actual aircraft tasking process, but in its continuous variable version, provides fast, nearly optimal solutions that should approximate real-world tasking results.

Keywords: decision analysis; applications; influence diagrams and decision trees; military; targeting; theater level air mission planning; programming; integer; assignment of aircraft and weapons to targets (search for similar items in EconPapers)
Date: 1997
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