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.
Agile Earth Observation Satellite Scheduling With a Quantum Annealer
IEEE Transactions on Aerospace and Electronic Systems ; 57 , 5 ; 3520-3528
2021-10-01
2691994 byte
Article (Journal)
Electronic Resource
English