基于改进遗传算法的星地任务优化调度研究

Research on scheduling of satellite-ground cooperating missions based on improved genetic algorithm

星地任务优化调度是利用特定的星地资源合理地安排星地任务。由于星地任务众多而资源有限,而且星地任务受星地可见性以及多方面约束,星地任务调度问题十分复杂。针对星地任务的特点,建立了星地任务调度问题模型,提出了基于改进遗传算法的星地任务优化调度算法。算法采用按适应度排名轮盘赌选择、顺序交叉、随机对换变异的算法要素。针对遗传算法局部搜索能力弱的特点,提出了利用爬山算法优化新一代个体的方法,以增强遗传算法的局部搜索能力,给出了基于改进遗传算法的星地任务调度算法。

The scheduling of satellite-ground cooperating missions is to arrange the missions scientifically, which uses the limited satellites and ground resources to fulfill. The scheduling is complex not only because of the access conditions between satellites and ground stations, but also because of the conflict between the large numbers of tasks and the limited resources. In this paper, a mathematical model of the satellite-ground cooperating scheduling problem is established con-sidering the features of the missions. And an improved genetic algorithm is presented to solve the scheduling problem. The algorithm includes rank-based fitness assignment and roulette wheel selection, ordered crossover, and random change mutation. By using hill-climbing methods, the local searching ability of the genetic algorithm is improved.