基于多目标优化的联合作战用频规划方法

为全面描述联合作战用频规划问题，引入多目标优化理论，以干扰冲突最少、需求满足最高和邻频风险最低作为优化目标建立了多目标的联合作战用频规划模型，并提出一种求解联合作战用频规划问题的非支配排序蚁群算法. 在蚁群初始化阶段使用带贪心策略的爬山算法获取次优解集合以提升蚁群前期收敛速度，并运用社团检测机制将用频装备分簇以减少电磁干扰分析的计算复杂度从而加快算法进程. 同时，在算法每次迭代中对得到的用频规划方案执行调度改进操作，并自适应调整信息素挥发系数等参数，以提升算法全局优化性能. 仿真实验验证了模型的有效性，并通过反转世代距离与超体积指标证明了算法在收敛性、分布性与收敛速度上的优越性.

Frequency planning method for joint operations based on multi-objective optimization

In order to describe the joint operation frequency planning problem comprehensively, the multi-objective optimization theory is introduced, and a multi-objective joint operation frequency planning model is established with the minimum interference conflict, the highest demand satisfaction and the lowest neighbor frequency risk as the optimization objectives. A non-dominated ordering ant colony algorithm is proposed to solve the joint operation frequency planning problem. In the initial stage of the ant colony, a mountain-climbing algorithm with a greedy strategy is used to obtain the suboptimal solution set to improve the early convergence rate of the ant colony. In order to reduce the computational complexity of EMI analysis and speed up the process of the algorithm, the frequency equipment is grouped by community detection mechanism. At the same time, in each iteration of the algorithm, an improved scheduling operation is performed for the obtained frequency planning scheme, and parameters such as pheromone volatility coefficient are adjusted adaptively to improve the global optimization performance of the algorithm. Simulation results verify the effectiveness of the model, and prove the superiority of the algorithm in convergence, distribution and convergence speed by inverted generational distance and hyper volume.