关键词: 果蝇算法, 优化, 最优值, 变化率, 收敛精度

Abstract: In order to solve the problems of low convergence precision and convergence rate of traditional fruit fly algorithm, a new improved FOA is proposed. This algorithm, through the iteration procedures, uses the optimal value of the rate as a reference of the fruit fly swarm, affecting the next flight distance. The changing flight distance of the fruit swarm dynamically can balance the global search ability and local search ability of the algorithm effectively. This algorithm is compared with the original FOA and other two improved FOA algorithms in the function optimization simulation process. Experimental results show that the new algorithm has obvious advantages in terms of convergence precision, convergence speed and stability.

Key words: fruit algorithm, optimization, optimal value, changing rate, convergence precision