大型星座混合模拟退火遗传算法测控任务规划

A hybrid simulated annealing genetic algorithm(HSAGA)based on congestion is proposed to solve the tracking,telemetry,and control(TT&C)scheduling problem of large constellations. Firstly,the constraints satisfy problem (CSP)model of TT&C scheduling is established by formally describing various constraints and optimization objectives. Secondly,multi-layer encoding method is adopted to map the TT&C schedule into integer sequence,and genetic algorithm is utilized to perform global optimization. Thirdly,in order to enhance population diversity and expedite convergence,at the end of each iteration,the optimal part of the population is processed with congestion-based simulated annealing. The algorithm is applied on real constellation for TT&C. The constellation consists of over 180 satellites and 32 antennas. The application demonstrates that the HSAGA exhibits a task completion rate exceeding 99%,a normalized integrated gain surpassing 0. 9,and a time consumption of less than 15 minutes,thereby validating the algorithm’s practical significance.