针对具有不同服务质量需求的用户，在全覆盖的要求下，提出一种超启发式灰狼算法，来寻求最少无人机数量的最优部署。首先推导无人机基站最大覆盖半径、最佳高度，确定无人机基站的最少数量；其次采用局部互利博弈来建模无人机基站部署问题，并证明该问题是一个精确势博弈过程，至少有一个纳什均衡点；最后，设计了一种基于势博弈的超启发式算法，通过多次迭代来逼近全覆盖要求下，最少无人机基站部署的纳什均衡点。仿真结果表明，所提出的解决方案在最小化无人机数量和加快收敛速度方面具有显著优势。
A 3D spatial deployment method for the optimal number of UAVs is proposed based on full coverage for users with different service quality requirements. The number of UAV base stations deployed is minimized by optimizing the 3D spatial location of UAV base stations. Firstly, the maximum service radius and the optimal height of UAV base stations are calculated. Secondly, a partial altruistic game is used to model the UAV deployment for purpose of proving that this research is an exact potential game process. Finally, the lower limit of the required number of UAV base stations is calculated, and an algorithm based on hyperheuristic methodology is designed to approximate by iteration the Nash equilibrium point under the maximum coverage requirement. The optimal de-ployment location of UAV base stations is then achieved, and the minimum number of UAV base stations with full coverage is determined. The simulation results show that the proposed solution has significant advantages in min-imizing the number of UAVs and accelerating the convergence speed.
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