超视距多目标攻击排序问题的蚁群算法

Ant Colony Algorithm for Solving Scheduling Problem in Multi-targets Attacking

针对现代超视距空战的指挥决策问题,提出一种基于蚁群算法思想的超视距多目标攻击的优化排序方法。该方法利用蚁群算法的并行计算和全局快速搜索能力,使超视距多目标攻击排序算法能够在限定时间内获得满意解,并给出应用该方法的具体实现步骤。仿真实验说明了该算法的有效性,特别当问题规模较大时,该算法具有较快的收敛速度和较高的精度。

Aiming at the command and decision-making problem in Beyond Visual Range Air Combat （BVRAC）, an optimal scheduling method of multi-targets BVR attacking based on ant colony algorithm is put forward. By applying the good parallel computing and fast global searching capabilities of ant colony algorithm, it makes the constructed scheduling method of multi-targets BVR attacking, which can obtain satisfaction solution to the problem in real time. The implement process is given. Simulation result shows that the method is effective, especially for large scale scheduling problem, and has faster constringency rate and higher precision.