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提出一种基于粒子群算法和方向加速法组合成的PSO-Powell算法,能进行大范围搜索,其最优解具有全局收敛性。在该算法中,对粒子群算法的参数设置进行了改进,提升了其性能,并引入增广拉格朗日乘子法处理优化问题的约束条件,提高了最优解的精度。仿真结果表明PSO-Powell算法应用于运载火箭弹道优化设计具有良好效果,可以提升运载能力,具有一定工程应用价值。
A PSO-Powell algorithm based on particle swarm optimization and directional acceleration is proposed, which can search a large area and the global convergence of the optimal solution. In this algorithm, the parameters of particle swarm optimization are improved to improve its performance, and the augmented Lagrange multiplier method is introduced to deal with the optimization constraints, which improves the precision of the optimal solution. The simulation results show that the PSO-Powell algorithm has good effect in ballistic optimization design of launch vehicle, which can improve the carrying capacity and has certain engineering application value.