Satellite Observing Mission Scheduling Method Based on Case-Based Learning and a Genetic Algorithm

Satellite observation scheduling is a complex combinational optimization problem. Current researches usually adopt intelligent optimization methods to solve it, ignoring the similar historical scheduling cases. In order to improve algorithm performance, case-based learning method is introduced to the scheduling process. Considering the characteristic of the problem, a method of retrieving, matching and revising satellite observing scheduling historical cases is designed. Then, a novel algorithm based on case-based learning and a genetic algorithm is proposed. Finally, some experiments are conducted to validate the correctness and practicability of our algorithm.