一种改进的鱼鹰优化算法  

Improved Osprey Optimization Algorithm

作　　者：邰志艳 邢维康 谷佳澄 刘铭 于晓东 TAI Zhiyan;XING Weikang;GU Jiacheng;LIU Ming;YU Xiaodong(School of Mathematics and Statistics,Changchun University of Technology,Changchun 130012,China;School of Information Science and Technology,Shanghai Sanda University,Shanghai 201209,China)

机构地区：[1]长春工业大学数学与统计学院,长春130012 [2]上海杉达学院信息科学与技术学院,上海201209

出　　处：《吉林大学学报(信息科学版)》2025年第1期126-133,共8页Journal of Jilin University(Information Science Edition)

基　　金：吉林省发改委基本建设资金资助项目(2022C043-2);吉林省自然科学基金资助项目(20200201157JC)。

摘　　要：针对原始鱼鹰优化算法(OOA:Osprey Optimization Algorithm)易陷入局部最优和寻优速度慢等问题,提出了一种改进鱼鹰优化算法(L_OOA:An Improved Osprey Optimization Algorithm)。首先,为保持种群多样性,采用了Tent混沌映射策略初始化种群个体位置。其次,通过引入Levy策略对鱼鹰的位置进行更新,提高了鱼鹰优化算法跳出局部最优值的能力,并在鱼鹰优化算法中引入了螺旋曲线策略,提升了算法计算精确度。最后,在CEC2021(Computational Experimental Competition 2021)测试函数集上与其他智能算法进行了对比实验。结果表明,L_OOA具有更优的精度和更快的速度。The L_OOA(An Improved Osprey Optimization Algorithm) is proposed to address the issues of the original OOA(Osprey Optimization Algorithm),which is prone to local optima and slow optimization speed.Firstly,to maintain population diversity,the Tent chaotic mapping strategy is adopted to initialize the individual positions of the population.Secondly,by introducing the Levy strategy to update the position of the Osprey,the Osprey Optimization Algorithm can improve its ability to jump out of local optima.The spiral curve strategy is introduced into the Osprey optimization algorithm to improve its computational accuracy.Finally,comparative experiments are conducted with other intelligent algorithms on the CEC2021(Computational Experimental Competition 2021)testfunction set.Experiments prove that L_OOA has better accuracy and faster speed.

关 键 词：鱼鹰优化算法 螺旋曲线策略 Levy策略 Tent混沌映射 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]