摘要
针对樽海鞘群算法求解精度不高和收敛速度慢等缺点,提出一种正弦余弦算法的樽海鞘群算法(SCSSA)。引入Logistics混沌序列生成初始种群,增加初始个体的多样性;将正弦余弦算法作为局部因子嵌入到樽海鞘群算法中,对樽海鞘个体进行正弦和余弦优化;对最优樽海鞘的领域空间进行差分演化变异策略,增强局部搜索能力。将改进算法在8个典型复杂函数优化问题上进行仿真实验,并同正弦余弦算法和樽海鞘群算法进行对比。实验结果表明,该算法具有更好全局搜索能力和局部搜索能力,寻优精度比标准算法有所增强。
For the disadvantages of low precision and slow convergence speed of salp swarm algorithm,we propose a salp swarm algorithm using sine and cosine algorithm(SCSSA).We introduced the chaotic sequence of logistics to generate the initial population,so as to increase the diversity of initial individuals.Then,in order to optimize the sine and cosine of the salp,the sine cosine algorithm was embedded as a local factor in the salp swarm algorithm.The differential evolution mutation strategy was carried out on the domain space of the optimal ascidian to enhance local search capabilities.The improved algorithm was simulated and tested on 8 typical complex function optimization problems,and compared with the sine cosine algorithm and the salp swarm algorithm.The results show that the SCSSA has better global and local searching ability,and its optimization accuracy is enhanced than the standard algorithm.
作者
陈忠云
张达敏
辛梓芸
Chen Zhongyun;Zhang Damin;Xin Ziyun(School of Big Data and Information Engineering,Guizhou University,Guiyang 550025,Guizhou,China)
出处
《计算机应用与软件》
北大核心
2020年第9期209-214,共6页
Computer Applications and Software
基金
贵州省自然科学基金项目(黔科合基础[2017]1047号)。
关键词
混沌映射
正弦余弦算法
樽海鞘群算法
差分演化变异
函数优化
Chaotic map
Sine cosine algorithm
Salp swarm algorithm
Differential evolutionary mutation
Function optimization
