  For complex combinatorial optimization problems, models and algorithms are at
the heart of the solution. The complexity of many types of satellite mission
planning problems is NP-hard and places high demands on the solution. In this
paper, two types of satellite scheduling problem models are introduced and a
reinforcement learning based evolutionary algorithm framework based is
proposed.

Neural and Evolutionary Computing;Artificial Intelligence;Optimization and Control