  The Synthetic Theater Operations Research Model (STORM) simulates
theater-level conflict and requires inputs about utilization of surveillance
satellites to search large geographical areas. We develop a mixed-integer
linear optimization model that prescribes plans for how satellites and their
sensors should be directed to best search an area of operations. It also
specifies the resolution levels employed by the sensors to ensure a suitable
fidelity of the resulting images. We solve large-scale instances of the model
involving up to 22 million variables and 11 million constraints in scenarios
derived from STORM. On average, the model yields 55% improvement in search
coverage relative to an existing heuristic algorithm in STORM.
