论文标题
优化合成剧院操作研究模型的监视卫星
Optimizing Surveillance Satellites for the Synthetic Theater Operations Research Model
论文作者
论文摘要
合成剧院运营研究模型（Storm）模拟了剧院级别的冲突，并需要有关利用监视卫星来搜索大型地理区域的投入。我们开发了一个混合的线性优化模型，该模型规定了应如何指示卫星及其传感器以最佳搜索操作领域的计划。它还指定了传感器采用的分辨率水平，以确保所得图像的合适保真度。我们解决了该模型的大规模实例，其中涉及多达2200万变量和1100万个限制，在风暴中得出的情况下。平均而言，相对于现有的启发式算法，该模型的搜索覆盖率提高了55％。
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.
