Abstract:

 Aiming at solving the problem of the large solution space and mixed decision variables on agile image satellites scheduling, a scheduling model with multi-decision variables is built, and an improved quantum genetic algorithm is proposed in this paper. The improved algorithm adopts a hybrid coding strategy, which combines the binary with the real number coding. The hybrid coding is more concise compared to the classic coding of the satellite scheduling. Based on the hybrid coding strategy, the observation functions are designed to map the solution space of the agile image satellites to the quantum space so that the agile image satellites scheduling problem could be solved effectively with the quantum optimization mechanism. In the end of this paper, the simulations in different sizes are performed to verify the proposed algorithm. The simulation results show that compared with the classic algorithms, the improved quantum genetic algorithm proposed in this paper has better performance in both quality and time efficiency.

Key words: Agile image satellites, Improved quantum genetic algorithm, Image satellite scheduling, Optimization problem with mixed decision variables