求解函数优化问题的新型果蝇算法

A novel Fruit Fly Optimization Algorithm for solving function optimization problems

由于果蝇优化算法(FOA算法)寻优精度低,易陷入局部最优,论文提出了一种基于速度变量的果蝇优化新算法(VFOA算法)。它以FOA算法为基础,利用果蝇的飞行特性,结合PSO算法中的粒子速度变量,构造VFOA算法。对4个标准测试函数进行仿真实验,结果表明:VFOA算法提高了收敛精度,加快了收敛速度。

Due to the low optimization accuracy of the Fruit Fly Optimization Algorithm （FOA）, it is easy to get into local optimum. This study proposes a fruit fly optimization algorithm based on velocity variables （VFOA）. Based on the FOA algorithm, the flight characteristics of Drosophila and the particle velocity variables in PSO algorithm are used to construct VFOA algorithm. Then four standard test functions are simulated. The experimental results show that VFOA algorithm accelerates the convergence accuracy and convergence speed of the fly optimization algorithm.