A tabu search algorithm for satellite imaging scheduling

This paper deals with the daily imaging scheduling problem for a low-orbit, earth observation satellite, which belongs to a class of single-machine scheduling problems. Its salient features include sequence-dependent setup effects, job-assembly characteristics, and time window constraints. Instead of looking for the global optimal solutions, we adopt a promising evolutionary approach, tabu search, to solve this scheduling problem. Numerical results demonstrate that the approach is effective and efficient in applications to the real problems.