Optimizing assignment of air-to-ground assets and bomb-damage assessment sensors

The advent of expensive precision weaponry and long-range strike warfare has increased the importance of bomb-damage assessment (BDA). While it is possible to overwhelm uncertainty with firepower, the Department of Defense has instead chosen to invest heavily in sensors and command-and-control systems to improve post-strike assessments. Unfortunately, the analysis community has found that finding the appropriate mix of BDA sensors and precision weapons has been a difficult challenge. In this article, Kirk Yost and Al Washburn present a new methodology for integrating BDA sensors and air-to-ground strike assets in a single optimization model. Their methodology combines a well known OR technique (linear programming), with a largely unused body of theory (partially observable Markov decision processes) to allow direct computation of an optimal sensor–shooter mix. This article discusses the warfighting issues, presents an overview of the theory, and gives results for notional major theater of war data set.