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中文摘要：
为了处理早熟的集中和慢集中的问题，评价在三维(3D ) 发送无人的天线车辆(UAV ) 计划低高度的穿入，计划方法的一条新奇线路被建议。首先，一个 coevolutionary 多代理人基因算法(CE-MAGA ) 被把 coevolutionary 机制介绍给多代理人形成基因算法(MAGA ) ，一个有效全球优化算法。一种动态线路表示形式也被采用改进飞行线路精确性。而且，处理方法的有效限制被用来简化多限制的处理并且减少计划的时间费用计算。模拟和计划 CE-MAGA 结果的相应分析表演在地面列在后面，比另外的存在算法的地面回避，威胁回避(TF/TA2 ) 和更低的线路费用上有更好的性能。另外，可行飞行线路能在 2 以内被获得 s，和整个进化过程的集中率是很快的。
英文摘要：
To address the issue of premature convergence and slow convergence rate in three-dimensional （3D） route planning of unmanned aerial vehicle （UAV） low-altitude penetration, a novel route planning method was proposed. First and foremost, a coevolutionary multi-agent genetic algorithm （CE-MAGA） was formed by introducing coevolutionary mechanism to multi-agent genetic algorithm （MAGA）, an efficient global optimization algorithm. A dynamic route representation form was also adopted to improve the flight route accuracy. Moreover, an efficient constraint handling method was used to simplify the treatment of multi-constraint and reduce the time-cost of planning computation. Simulation and corresponding analysis show that the planning results of CE-MAGA have better performance on terrain following, terrain avoidance, threat avoidance （TF/TA2） and lower route costs than other existing algorithms. In addition, feasible flight routes can be acquired within 2 s, and the convergence rate of the whole evolutionary process is very fast.
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