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为解决天基预警系统中的卫星资源调度问题,从预警任务特点出发,在对预警任务进行分解的基础上,建立了资源调度模型.结合传统遗传算法(GA)和粒子群算法(PSO)的优点,采用一种混合遗传粒子群(GA-PSO)算法来求解资源调度问题.该算法在解决粒子编解码问题的前提下,将遗传算法的遗传算子应用于粒子群算法,改善了粒子群算法的寻优能力.实验结果表明,提出的算法能有效解决多目标探测时天基预警系统的资源调度问题,调度结果优于传统粒子群算法和遗传算法.
In order to solve the problem of satellite resource scheduling in the space-based early-warning system, a resource scheduling model is established based on the characteristics of the early-warning task and the early-warning task.According to the traditional genetic algorithm (GA) and particle swarm optimization (PSO) Advantages, a hybrid genetic particle swarm optimization (GA-PSO) algorithm is used to solve the resource scheduling problem.Based on the problem of particle codec, the genetic algorithm is applied to the particle swarm optimization algorithm to improve the particle swarm optimization The experimental results show that the proposed algorithm can effectively solve the resource scheduling problem of the space-based early-warning system in multi-target detection, and the scheduling result is better than the traditional particle swarm optimization and genetic algorithm.