Research on Multi-Satellite Mission Planning Based on Improved Genetic Algorithm - Yang, Yang; Liu, Desheng (2022 3rd International Conference on Computer Science and Management Technology (ICCSMT), 2022)
For the multi-satellite mission planning problem, a multi-satellite mission planning model is constructed by considering the constraints of satellite's visibility window to the target, attitude transition, storage and energy consumption, and an improved genetic algorithm is proposed to solve the model. The algorithm adopts the real number coding method to improve the solution efficiency, introduces the adaptive mechanism and the elite retention strategy, which improves the problems that the genetic algorithm is easy to fall into local optimum and converge early. The effectiveness of the improved genetic algorithm for solving multi-star mission planning is verified through simulation case analysis, and it is compared and analyzed with the standard genetic algorithm. The results show that the well genetic algorithm can achieve faster convergence and better planning results, and has better adaptability to large-scale mission planning problems.