计算机应用与软件Issue(1)：283-285,302,4.DOI:10.3969/j.issn.1000-386x.2014.01.076
基于改进萤火虫算法的多模函数优化
MULTIMODAL FUNCTION OPTIMISATION BASED ON IMPROVED GLOWWORM SWARM OPTIMISATION
吴伟民 1亢少将 1林志毅 1郭涛1
作者信息
- 1. 广东工业大学计算机学院 广东 广州510006
- 折叠
摘要
Abstract
In order to improve the performance of multimodal function optimisation with glowworm swarm optimisation (GSO),and to solve the problems of GSO in low peaks discovery rate,slow convergence speed and low computational accuracy,we propose an improved glowworm swarm optimisation (IGSO),in which the individual glowworm (agent)can adaptively search the peaks,and its moving step is variable.The IGSO introduces the tentative moving strategy to enhance the searching ability of the algorithm,and meantime it uses average neighbourhood distance as the reference to adjust agent’s moving step.The results of experiment on typical multimodal functions indicate that the IGSO is superior to GSO in multimodal function optimisation with high peaks discovery rate,fast convergence speed and high computational accuracy.关键词
GSO/IGSO/多模函数/移动步长Key words
GSO/IGSO/Multimodal function/Moving step分类
信息技术与安全科学引用本文复制引用
吴伟民,亢少将,林志毅,郭涛..基于改进萤火虫算法的多模函数优化[J].计算机应用与软件,2014,(1):283-285,302,4.
