摘要
针对鲸鱼优化算法(WOA)存在收敛精度低和收敛速度慢的问题,提出基于混沌权重和精英引导的先进鲸鱼优化算法(AWOA)。考虑算法前期搜索的随机性对收敛速度的影响,引入精英个体引导机制,利用精英个体的进化反馈信息及时调整种群的搜索方向,加强算法的全局搜索能力。在算法后期引入混沌动态权重因子加强算法的局部搜索能力,提高算法的收敛精度,对多个基准测试函数进行对比仿真实验,结果表明:改进的鲸鱼算法具有更高的寻优性能。
Aiming at the problems of low convergence precision and slow convergence speed of whale optimization algorithm(WOA),an advanced WOA(AWOA)based on chaotic weight and elite guidance is proposed.Considering the influence of randomicity of pre-search on convergence speed,elite individual guidance mechanism is introduced,and the evolutionary feedback information of elite individuals is used to adjust the search direction of the population in time,so as to enhance the global search ability of the algorithm.Chaotic dynamic weight factor is introduced to enhance the local search ability and improve the convergence precision of the algorithm.Simulation results of several benchmark functions show that the improved whale algorithm has better optimization performance.
作者
黄辉先
张广炎
陈思溢
胡拚
HUANG Huixian;ZHANG Guangyan;CHEN Siyi;HU Pin(School of Information Engineering,Xiangtan University,Xiangtan 411105,China)
出处
《传感器与微系统》
CSCD
2020年第5期113-116,共4页
Transducer and Microsystem Technologies
基金
国家部委预先研究基金资助项目(20170101)。
关键词
鲸鱼优化算法
精英个体
进化反馈
混沌动态权重
whale optimization algorithm(WOA)
elite individuals
evolutionary feedback
chaotic dynamic weight
