基于并行禁忌遗传算法(PTGA)的预警卫星传感器调度研究

对预警卫星的传感器调度进行了研究，提出了传感器管理调度的系统组成。通过对传感器调度的分析，建立起相应的数学模型，定义了评价指标。结合并行遗传算法和禁忌搜索的特点，提出了一种新的解决预警卫星传感器调度问题的并行禁忌遗传算法(PTGA)。该算法采用多种群和禁忌搜索思想改进遗传算法的性能，从而提高整个算法的收敛速度和精度。实验结果表明该算法有效地解决了多目标情况下的传感器实时调度问题，并优于一般启发式算法。

Study of sensor scheduling for early warning satellite based on parallel tabu genetic algorithm (PTGA)

Sensor scheduling for early warning satellite has been studied,and the system of sensor management and scheduling was built.Through analyzing the working environment,the mathematic model of sensor scheduling for multiple objects was built,and the evaluation index was defined.Based on the combination of parallel genetic algorithm and tabu search,an optimal search approach for early warning satellite's sensor scheduling,a novel parallel tabu genetic algorithm (PTGA) was given.Paralleling multiple groups increased the running speed,and tabu search was introduced into the operation of crossover and mutation,which could improve the convergence precision.By building the list of objects and sensors,the problem of sensor rescheduling could be solved when a new object occurred.Experimental results show that the algorithm can effectively deal with the real time sensor scheduling under the circumstances of multiple objects,and it is better than other heuristic algorithms.