一种改进的鲸鱼优化算法在工程上的应用  

Application of an Improved Whale Optimization Algorithm in Engineering

作　　者：林恒青[1] LIN Heng-qing(College of Mechanical and Intelligent Manufacturing,Fujian Chuanzheng Communications College,Fuzhou 350007,China)

机构地区：[1]福建船政交通职业学院机械与智能制造学院,福建福州350007

出　　处：《兰州文理学院学报（自然科学版）》2024年第3期44-47,53,共5页Journal of Lanzhou University of Arts and Science(Natural Sciences)

基　　金：2020年福建省教育厅中青年教师教育科研项目(JAT201062)。

摘　　要：针对鲸鱼优化算法存在收敛速度慢、易于陷入局部最优、收敛精度不高等问题,提出一种混合策略的改进鲸鱼优化算法(LWWOA).首先在全局搜索阶段引入莱维飞行,然后在螺旋更新阶段加入一个随机调整的惯性权重,最后将改进的鲸鱼优化算法应用于实际工程的优化设计问题,应用场景包括三杆桁架设计和压力弹簧的设计.仿真结果表明,LWWOA具有较快的收敛速度和较优的收敛精度,对实际工程的设计具有指导意义,并能拓展到其他领域.The Whale Optimization Algorithm is a newly proposed population intelligence algorithm in recent years,which has problems such as slow convergence speed,easy to fall into local optima,and low convergence accuracy.In response to the above issues,this article proposes a hybrid strategy based improved whale optimization algorithm(LWWOA),which first introduces Levy flight in the global search phase,and then adds a randomly adjusted inertia weight in the spiral update phase,at last,applies the improved whale optimization algorithm to practical engineering optimization design problems,including the design of three bar trusses and the design of pressure springs.The simulation results show that LWWOA has a fast convergence speed and excellent convergence accuracy,which has guiding significance for practical engineering design and can be extended to other fields.

关 键 词：鲸鱼优化算法 莱维飞行 惯性权重策略 三杆桁架 压力弹簧 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]