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.