以数据中继卫星光网络系统资源、任务和约束条件为参量，以任务对资源的选择为优化对象，提出了一种基于自适应遗传算法的数据中继卫星光网络资源调度算法。综合考虑多中继星、多时间窗口、多光学天线以及任务优先级要求，建立调度模型；采用“当前任务调度时间的确定”和“后续任务可见时间窗口的更新”的调度操作，对不同资源的任务集合进行调度安排并实现了可见时间窗口的动态更新，获得调度任务的总权值并将其作为参量计算适应度值，最后通过改进的自适应遗传算法对不同调度方案进行寻优。以3颗中继星、12颗用户星，6个光天线，60个任务为条件设置了仿真场景，仿真结果表明该算法在收敛速度、调度效率方面具有优势，适应于多任务、多天线的数据中继卫星光网络系统资源调度。

According to the resources, missions and restraints of the data relay satellite optical network, a scheduling algorithm based on improved self-adaptive genetic algorithm was put forwarded. Considering the multi-relay satellite, multi-window, multi-optical-antenna and multi-mission PRI, the model was established. The missions were scheduled by the scheduling operates: the ascertainment of current mission scheduling time and the refreshment of latter mission time-window. The whole weight of the scheduled missions was set as the cost value and the scheduling schemes were optimized by the self-adaptive genetic algorithm. The simulation scene including 3 relay satellites, 12 user satellites, 6 antennas and 60 missions, the result reveals that the algorithm obtains satisfactory results in both time and optimization which is suitable in multi-user, multi-mission and multi-optical-antenna recourse scheduling.