首页|基于混沌精英和Lévy飞行策略的鲸鱼优化算法

基于混沌精英和Lévy飞行策略的鲸鱼优化算法

Whale Optimization Algorithm Based on Chaotic Elite and Lévy Flight Strategy

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针对鲸鱼优化算法(Whale Optimization Algorithm,WOA)存在的收敛速度慢、精度低的问题,提出了基于Tent混沌精英和Lévy飞行策略的鲸鱼优化算法(TELWOA).使用Tent混沌映射初始化鲸鱼种群,保持种群的多样性,并通过引入精英反向学习策略,对初始种群的精英个体生成反向解,选取适应度高的种群作为下一代鲸鱼种群,加快算法收敛速度.其次,通过使用非线性收敛因子,缓解算法全局搜索和局部搜索能力不平衡的现象.最后,在鲸鱼位置寻优过程中使用Lévy飞行策略,避免算法陷入局部最优,提升算法的全局搜索能力.通过对不同改进策略的有效性分析、与其他智能算法的对比分析,证明了 TELWOA算法在收敛精度、算法稳定性和全局寻优能力上与对比算法有显著提升,具有一定的实际工程应用能力.
For the problems of slow convergence and low accuracy of Whale Optimization Algorithm(WO A),the WO A based on Tent chaotic Elite and Lévy flight strategy(TELWOA)is proposed.The whale population is initialized by Tent chaotic mapping to maintain the population diversity,and the algorithm convergence speed is accelerated by introducing an elite opposition-based learning strategy to generate the inverse solution for the elite individuals of the initial population and select the population with high adaptation as the next generation whale population.Secondly,by using a nonlinear convergence factor,the imbalance between the algorithm's global search and local search ability is alleviated.Finally,the Lévy flight strategy is used in the whale location search process to avoid the algorithm from falling into local optimum and to improve the global search ability of the algorithm.By analyzing the effectiveness of different improvement strategies and comparing with other intelligent algorithms,it is proved that TELWOA has significant improvement in convergence accuracy,algorithmic stability and global optimization searching ability with comparison algorithms,and it has certain practical engineering application ability.

whale optimization algorithmTent chaotic mappingopposition-based learningnonlinear convergence factorLévy flight strategy

夏超、欧阳平、李明、屈盈飞、郭玮峰

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重庆工商大学 废油资源化技术与装备教育部工程研究中心,重庆 400067

重庆工商大学 检测控制集成系统工程实验室,重庆 400067

重庆工商大学 人工智能学院,重庆 400067

鲸鱼优化算法 Tent混沌映射 反向学习策略 非线性收敛因子 Lévy飞行策略

重庆市教委重大科技项目重庆市教委科技项目重庆市研究生创新科研项目

KJZD-M202200801KJQN202200828yjscxx2023-211-120

2024

10.20165/j.cnki.ISSN1673-629X.2024.0027

计算机技术与发展
陕西省计算机学会

计算机技术与发展

CSTPCD
影响因子：0.621
ISSN：1673-629X
年,卷(期)：2024.34(4)
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