Combinatorial optimization for spacecraft scheduling

The application of combinatorial optimization techniques to the automatic spacecraft scheduling problem is described. The problem is to search over the candidate sequences of experiments for a sequence that maximizes the value of the science conducted while minimizing constraint conflicts. Exploratory computational results indicate that pseudorandom research techniques, such as simulated annealing, generate viable sequences in reasonable times.<>