We present a comparison study of state-of-the-art classical optimization methods to a D-Wave 2000Q quantum annealer for the scheduling of agile Earth observation satellites. The problem is to acquire high-value images while obeying the attitude maneuvering constraint of the satellite. In order to investigate close to real-world problems, we created benchmark problems by simulating realistic scenarios. Our results show that a tuned quantum annealing approach can run faster when used to find the optimal solution than a classical exact solver for some of the problem instances. Moreover, we find that the solution quality of the quantum annealer is comparable to the heuristic method used operationally for small problem instances, but degrades rapidly due to the limited precision of the quantum annealer.

中文翻译：

---

使用量子退火器进行敏捷地球观测卫星调度


我们对最先进的经典优化方法与用于敏捷地球观测卫星调度的 D-Wave 2000Q 量子退火器进行了比较研究。问题是在遵守卫星姿态机动约束的同时获取高价值图像。为了研究接近现实世界的问题，我们通过模拟现实场景创建基准问题。我们的结果表明，对于某些问题实例，调整量子退火方法在用于寻找最佳解决方案时比经典精确求解器运行得更快。此外，我们发现量子退火器的解质量与针对小问题实例操作使用的启发式方法相当，但由于量子退火器的精度有限，解质量迅速下降。