面向深空探测任务的实数遗传编码多星任务规划算法

Aiming at the multi-star mission planning problem for deep space exploration missions, considering the constraints of satellite on target time window, satellite attitude maneuver and working energy consumption, a multi-star mission planning problem model for deep space exploration mission is established. In the process of large-scale satellite mission planning, the existing coding length is too long. A genetic algorithm based on real coding is proposed to solve the multi-star mission planning problem for deep space exploration. The algorithm adopts a real-number coding method with the target as the chromosome. Compared with the traditional 01 coding method with the time window as the chromosome, the chromosome length is shortened, which can effectively improve the efficiency of the algorithm. Through the numerical example analysis, the correctness, rationality and effectiveness of the genetic algorithm based on real number coding for solving multi-star task planning problems are verified. Compared with the genetic algorithm based on traditional 01 coding method, the results show that the genetic algorithm based on real coding has obvious advantages in optimization ability and calculation speed. This provides a new idea and method for solving multi-star mission planning problems for deep space exploration missions.