摘要
针对萤火虫群优化(GSO)算法优化多模态函数存在收敛速度慢和求解精度低等缺陷,提出一种自适应步长萤火虫群多模态函数优化算法(SASGSO)。该算法解决了萤火虫群优化(GSO)算法优化多模态函数所存在的不足;同时SASGSO算法也可找到多模态函数的所有极值点。数值实验仿真表明,该算法具有操作简单、易理解、收敛速度快和求解精度高等优点。
Because the GSO algorithm has slow convergence and low precision defects when optimizing the multi-modal function,a self-adaptive step glowworm swarm optimization（SASGSO） algorithms was proposed in this paper.This algorithm can overcome slow convergence and low precision defects of the GSO algorithm simultaneously it can find all peaks of the multi-modal function.Experiments show that,the SASGSO algorithm has the advantages of simple operation,easy to understand,fast convergence rates and high precision.
出处
《计算机科学》
CSCD
北大核心
2011年第7期220-224,共5页
Computer Science
基金
广西自然科学基金项目(0991086)
国家民委科研项目基金(08GX01)资助
