ISR Strategy Optimizer

This research effort will develop technology for optimizing strategy selection for a set of airborne intelligence collection platforms. This problem is important because of the need to maintain precise situational awareness of the battlespace given limited assets of different types/capabilities. Developing, analyzing, and comparing multiple strategies is difficult because of the large number of strategy dependent variables and the overwhelming complexity of the collection planning problem. To optimize strategy selection, we cast the collection planning problem as a grid-based network program and extend that formulation to include strategic variables (e.g., bed down locations, number/type of assets) and additional restrictions (e.g., threat zones). Solving this network program will provide important strategic direction concerning the optimal mix of assets, optimal bed down locations, and sensitivity to problem parameters such as threat zones; as well as provide a rapid estimate of the expected collection performance. Phase I will demonstrate a methodology for optimizing strategy selection based upon large-scale combinatorial optimization. We will implement a capability to view multiple strategies including tradeoffs of strategic variables with a graphical display of the results. Phase II will implement a more comprehensive solution methodology and develop a plan for insertion into theater-level collection management systems.