太赫兹科学与电子信息学报2016，Vol.14Issue(4)：610-614,5.DOI:10.11805/TKYDA201604.0610
自适应果蝇优化算法
Self-Adaptive Fruit Fly Optimization Algorithm
任新涛 1魏五洲 1杨宁国1
作者信息
- 1. 中国白城兵器试验中心，吉林白城 137001
- 折叠
摘要
Abstract
A Self-Adaptive Fruit Fly Optimization Algorithm(SAFOA) is proposed in order to further improve the performance of Fruit Fly Optimization Algorithm(FOA). A fruit fly search group pattern is designed, and then a self-adaptive variable-step search algorithm is put forward. Simulation results indicate that SAFOA features fast rate of convergence, strong global search and local optimization performance, and high convergence precision in comparison with FOA and Diminishing Step Fruit Fly Optimization Algorithm(DS-FOA).关键词
果蝇优化算法/自适应搜索步长/搜索群体/收敛速度Key words
Fruit Fly Optimization Algorithm/self-adaptive variable-step/search group/rate of convergence分类
信息技术与安全科学引用本文复制引用
任新涛,魏五洲,杨宁国..自适应果蝇优化算法[J].太赫兹科学与电子信息学报,2016,14(4):610-614,5.
