摘要
针对基本海鸥算法存在的缺陷,提出一种融合改进Logistics混沌和正弦余弦算子的自适应t分布海鸥算法(ISOA).首先,采用改进Logistics混沌映射初始化种群,使海鸥更加均匀地分布于初始解空间;其次,在海鸥位置更新方式中引入正弦余弦算子来协调算法的局部搜索和全局搜索,同时加入改进的参数A加快算法收敛速度;然后,引入自适应t分布变异策略,在最优解位置进行扰动变异产生新解,增强算法跳出局部最优的能力;最后,基于8个标准测试函数与3种基本算法进行对比仿真实验,结果表明ISOA与其余3种算法相比,有较强的跳出局部最优能力,收敛速度更快,精度更高.
Aiming at the defects of the basic seagull optimization algorithm,an adaptive T-distribution seagull optimization algorithm(ISOA)is proposed,which integrates improved Logistics chaos and sine and cosine operators.Firstly,the improved Logistics chaotic map is used to initialize the population,which lays the foundation for global optimization.Secondly,the local search and global search of the coordination algorithm of sine and cosine operators are introduced into the optimal seagull position updating method,and the improved parameter A is added to speed up the convergence rate.Then,the adaptive T-distribution mutation strategy is introduced to generate new solutions by perturbation mutation at the location of the optimal solution to enhance the ability of the algorithm to jump out of the local optimal solution.Finally,based on the eight standard test functions and the three basic algorithms,the simulation results show that compared with the other three algorithms,ISOA has a stronger ability to jump out of the local optimal,faster convergence speed and higher accuracy.
作者
毛清华
王迎港
MAO Qing-hua;WANG Ying-gang(School of Economics and Management,Yanshan University,Qinhuangdao 066004,China)
出处
《小型微型计算机系统》
CSCD
北大核心
2022年第11期2271-2277,共7页
Journal of Chinese Computer Systems
基金
国家自然科学基金项目(71704151)资助
河北省省级科技计划软科学研究专项项目(215576116D)资助。
