In order to solve the problem of multiple air refueling mission planning in the execution of long-range raiding missions, a multi-point air refueling model was established considering the timeliness and economy of the task. The differential evolution algorithm is improved by using the strategy of adaptively changing parameters, which makes it have faster search speed and computational efficiency. Simulation results show that the proposed method can effectively solve the problem of selecting fuel point in aircraft multi-point aerial refueling mission.
The traditional ant colony algorithm is prone to problems such as long search time and many turning points in the path when searching on the grid map. In this paper, a map modeling method is proposed, which combines Voronoi diagram to construct feasible paths and threat circle to describe obstacle areas. At the same time, the initial pheromone concentration of nodes is set differently, and the path is optimized by the point-by-point method. The experimental results show that the proposed method can effectively improve the ant colony algorithm and make it more suitable for UAV flight in battlefield environment.
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