文化算法在有人/无人机协同作战目标分配中的应用

Research on Problems of Manned/Unmanned Aerial Vehicle Cooperative Targets Assignment

针对有人/无人机协同作战目标分配问题,基于文化算法提出一种遗传算法和离散粒子群算法相结合的目标分配方法。根据有人/无人机协同目标分配问题的特性,结合文化算法的基本框架,建立了遗传算法和离散粒子群算法的交互机制,充分利用遗传算法和离散粒子群算法对优化问题的搜索能力,改善了2种算法易陷入局部最优的缺点,对约束条件下的有人/无人机协同作战目标分配问题进行了有效求解。实验结果表明,基于遗传和离散粒子群相结合的文化算法优于遗传算法和粒子群算法,收敛速度更快,能够快速找到目标分配问题的最优解。

A target assignment method, interaction mechanism of the genetic algorithm （GA） combined with the discrete particle swarm optimization （DPSO） is put forward based on cultural algorithm （CA）. According to the characteristics of MAV/UAV target assignment problem, the interaction mecha- nism between GA and DPSO is established based on the basic framework of CA. The proposed algorithm improves the search ability and overcomes easily to run into partial optimization. The algorithm can solve the MAV/UAV cooperation mission assignment problem effectively. The simulation results show that the proposed algorithm is better than GA and DPSO. The algorithm has a good convergence rate and can find the best assignment scheme fleetly.