一种改进的原子搜索算法  

An Improved Atomic Search Algorithm

作　　者：李建锋 卢迪[1] 李贺香 Li Jianfeng;Lu Di;Li Hexiang(School of Electrical and Electronic Engineering,Harbin University of Science and Technology,Harbin 150000,China)

机构地区：[1]哈尔滨理工大学电气与电子工程学院,黑龙江哈尔滨150000

出　　处：《系统仿真学报》2022年第3期490-502,共13页Journal of System Simulation

摘　　要：原子搜索算法(atom search algorithm,ASO)是模仿自然界中原子运动而提出的一种新型优化算法,针对ASO在求解复杂函数时存在易早熟及收敛速度慢的问题,提出了一种改进ASO算法(improved atomic search algorithm,IASO)。IASO加入了原子个体历史最优解产生的约束力来修正ASO的加速度,增强全局搜索能力。自适应更新2个乘数系数来协调算法的全局搜索和局部开发能力。适时采用高斯变异策略来重新更新原子位置,提高跳出早熟的能力。对14个基准函数进行仿真实验,对比其他算法,IASO在收敛速度、收敛精度方面表现出优越的性能。The atom search algorithm(ASO)is a new optimization algorithm proposed by imitating the movement of atoms in the natural world.An improved atomic search algorithm(IASO)is proposed to address the problems of prematureness and slow convergence of ASO in solving complex functions.IASO adds the binding force generated by the historical optimal solution of individual atoms to correct the acceleration of ASO and enhance the global search capability.The two multiplier coefficients are adaptively updated to coordinate the algorithm's global search and local development capabilities.The Gaussian mutation strategy is used to re-update the atomic position and improve the ability to jump out of precocity.Carrying out simulation experiments on 14 benchmark functions and comparing other algorithms,IASO shows superior performance in terms of convergence speed and convergence accuracy.

关 键 词：原子优化算法 函数优化 自适应 高斯变异 收敛精度 测试函数 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构] TP391.9[自动化与计算机技术—计算机科学与技术]