Abstract

In this paper, a scheduling optimization algorithm is developed and verified for autonomous satellite mission operations. As satellite control and operational techniques continue to develop, satellite missions become more complicated and the overall quantity of tasks within the missions also increases. These changes require more specific consideration and a huge amount of computational resources, for scheduling the satellite missions. In addition, there is a certain level of repetition in satellite mission scheduling activities, and hence it is highly recommended that the operation manager carefully considers and builds some appropriate strategy for performing the operations autonomously. A good strategy to adopt is to develop scheduling optimization algorithms, because it is difficult for humans to consider the many mission parameters and constraints simultaneously. In this paper, a new genetic algorithm is applied to simulations of an actual satellite mission scheduling problem, and an appropriate GUI design is considered for an autonomous satellite mission operation. It is expected that the scheduling optimization algorithm and the GUI can improve the overall efficiency in practical satellite mission operations.

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