Daily imaging scheduling of an Earth observation satellite

This work presents the development of a daily imaging scheduling system for a low-orbit, Earth observation satellite. The daily imaging scheduling problem of satellite considers various imaging requests with different reward opportunities, changeover efforts between two consecutive imaging tasks, cloud-coverage effects, and the availability of the spacecraft resource. It belongs to a class of single-machine scheduling problems with salient features of sequence-dependent setup, job assembly, and the constraint of operating time windows. The scheduling problem is formulated as an integer-programming problem, which is NP-hard in computational complexity. Lagrangian relaxation and linear search techniques are adopted to solve this problem. In order to demonstrate the efficiency and effectiveness of our solution methodology, a Tabu search-based algorithm is implemented, which is modified from the algorithm in Vasquez and Hao, 2001. Numerical results indicate that the approach is very effective to generate a near-optimal, feasible schedule for the imaging operations of the satellite. It is efficient in applications to the real problems. The Lagrangian-relaxation approach is superior to the Tabu search one in both optimality and computation time.