摘要
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.
作者
段国荣
刘元会
王亚萍
DUAN Guo-rong;LIU Yuan-hui;WANG Ya-ping(College of Science,Chang'an University,Xi'an 710064,China)
出处
《河南城建学院学报》
CAS
2018年第5期88-92,共5页
Journal of Henan University of Urban Construction
基金
国家自然科学基金项目(11401045)
关键词
果蝇算法
速度变量
非线性函数
fruit flies algorithm
velocity variable
nonlinear function