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针对无人机航路规划问题,研究了一种基于元胞蚂蚁算法的无人机航路规划方法。元胞蚂蚁算法对基本蚁群算法进行了系列改进,并将元胞邻居演化和改进后的蚂蚁寻优相结合,有效地克服了基本蚁群算法的收敛速度慢、易于过早陷入局部最优的缺点,提高了算法的运算精度,从而为解决复杂战场环境下无人机航路规划这一多约束多目标优化问题提供了一条可行的途径。
In order to solve the UAV route planning problem, a UAV route planning method based on cellular ant algorithm is studied. The cellular ant algorithm makes a series of improvements to the basic ant colony algorithm, and combines the cellular neighbors evolution with the improved ant optimization, which effectively overcomes the slow convergence rate of the basic ant colony algorithm and easy premature fall into the local optimum , Which improves the arithmetic precision of the algorithm and thus provides a feasible approach to solve the multi-constrained multi-objective optimization problem of UAV route planning in complex battlefield environment.