基于遗传算法的多UCAV动态任务分配研究

Research on Dynamic Multi-UCAVs Task Assignment Based on Genetic Algorithm

摘要:

为了使多无人作战飞机在复杂多变的动态战场环境下协同性、实时性更优,文章针对多无人作战飞机动态任务分配问题建立了一种扩展的多目标整数规划模型,同时设计了基于模糊集隶属度的混合重调度方法,并采用遗传算法进行求解；对无人作战飞机失效和出现新目标两种动态情况进行仿真实验,与完全重调度进行对比,得到基于模糊集隶属度的混合重调度方法在效率及稳定性方面明显优于完全重调度,说明设计的混合重调度方法及模型在解决多无人作战飞机动态任务分配问题上的有效性。

Abstract:

In order to make a better cooperativity and real-time performance of multi unmanned combat aerial vehicle (UCAV) in the dynamic complexity environment, an extension model of Multi-objective Integer Programming(MOIP) is established for the multiple UCAV, and designed a hybrid scheduling method based on fuzzy membership degree,then the problem is solved using the genetic algorithm(GA).Aiming at two dynamic condition of UCAV failure and new target appear, an simulation is performed. Compared with the full weight scheduling, the hybrid scheduling method based on fuzzy membership degree is superior to the full weight scheduling on efficiency and stability, which explain the effectiveness of the hybrid scheduling and model designed in solving the dynamic task allocation problem of multi UCAV.