智能系统学报Issue(3)：470-475,6.DOI:10.3969/j.issn.1673-4785.201403025
一种改进的自适应步长的人工萤火虫算法
An improved adaptive step glowworm swarm optimization algorithm
摘要
Abstract
In the basic glowworm swarm optimization ( GSO) , it is easy to fall into local optimum and the oscillation phenomenon of function adaptive values may occur because of the fixed step length. In some adaptive⁃step glowworm swarm optimization ( A⁃GSO) algorithms, neighborhood sets of some fireflies may be empty in the iterative process of the algorithm, which leads to lower convergence speed and falls into local optimal value. Therefore, an improved foraging⁃behavior adaptive⁃step GSO ( FA⁃GSO) algorithm was designed. The foraging behavior of the fireflies with⁃out neighborhood peer and adaptive step is introduced in order to find the optimization direction in the improved al⁃gorithm. The precision, stability, and global convergence analysis of FA⁃GSO is presented. After extracting and comparing the relevant optimization indicators of GSO, A⁃GSO and FA⁃GSO by several standard test functions, the effectiveness of the FA⁃GSO algorithm was verified, which indicates that the improved algorithm can improve the accuracy of function optimization and the iteration speed.关键词
人工萤火虫算法/自适应步长/觅食行为/全局收敛性Key words
glowworm swarm optimization/adaptive step/foraging behavior/global convergence分类
信息技术与安全科学引用本文复制引用
唐少虎,刘小明..一种改进的自适应步长的人工萤火虫算法[J].智能系统学报,2015,(3):470-475,6.基金项目
国家自然科学基金资助项目（61374191）；国家“863”计划资助项目（2012AA112401）；“十二五”国家科技支撑计划课题专项经费资助项目（2014BAG03B01）． （）
