非线性权重和收敛因子的鲸鱼算法
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摘要
针对鲸鱼优化算法收敛速度慢,收敛精度低等问题,提出一种基于非线性收敛因子和惯性权重的鲸鱼优化算法.首先使用改进后的Logistic混沌映射来初始化种群,增加种群多样性.然后将线性变化的收敛因子改进为一种分段式非线性收敛因子,同时增加了非线性惯性权重来增强算法的勘探和开发能力.最后选取7个基准函数进行测试,实验表明改进后算法收敛速度快、精度高.
To overcome the problems of slow convergence,slow accuracy of the standard whale optimization algorithm,a nonlinear weight and a nonlinear convergence factor in whale optimization algorithm is proposed.Firstly,the improved Logistic chaotic mapping is applied to initial population.Then the linearly variable convergence factor is improved to a piecewise nonlinear convergence factor.At the same time,nonlinear inertia weights are added to enhance the exploration and exploitation capabilities of the whale optimization algorithm.Finally,seven benchmark functions are selected for testing.Experiments show that the improved algorithm has fast convergence and high precision.
To overcome the problems of slow convergence,slow accuracy of the standard whale optimization algorithm,a nonlinear weight and a nonlinear convergence factor in whale optimization algorithm is proposed.Firstly,the improved Logistic chaotic mapping is applied to initial population.Then the linearly variable convergence factor is improved to a piecewise nonlinear convergence factor.At the same time,nonlinear inertia weights are added to enhance the exploration and exploitation capabilities of the whale optimization algorithm.Finally,seven benchmark functions are selected for testing.Experiments show that the improved algorithm has fast convergence and high precision.
引文
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[2] Mostafa A,Hassanien A E,Houseni M,et al.Liver segmentation in MRI images based on whale optimization algorithm[J].Multimedia Tools and Applications,2017,76(23):24931-24954.
[3] El Aziz M A,Ewees A A,Hassanien A E.Whale optimization algorithm and moth-flame optimization for multilevel thresholding image segmentation[J].Expert Systems with Applications, 2017(83):242-256.
[4] Prakash D B,Lakshminarayana C.Optimal siting of capacitors in radial distribution network using whale optimization algorithm[J].Alexandria Engineering Journal,2017,56(4):499-509.
[5]徐继亚,王艳,纪志成.基于鲸鱼算法优化WKELM的滚动轴承故障诊断[J].系统仿真学报,2017,29(9):2189-2197.
[6] Trivedi I N,Pradeep J,Narottam J,et al.Novel adaptive whale optimization algorithm for global optimization[J].Indian Journal of Science and Technology,2016,9(38):10.17485/ijst/2016/v9i38/101939.
[7] Kaveh A,Ghazaan M I.Enhanced whale optimization algorithm for sizing optimization of skeletal structures[J].Mechanics Based Design of Structures and Machines,2017,45(3):345-362.
[8] Oliva D,El Aziz M A,Hassanien A E.Parameter estimation of photovoltaic cells using an improved chaotic whale optimization algorithm[J].Applied Energy,2017(200):141-154.
[9]刘竹松,李生.正余混沌双弦鲸鱼优化算法[J].计算机工程与应用,2018,54(7):159-163.
[10]牛培峰,吴志良,马云鹏,等.基于鲸鱼优化算法的汽轮机热耗率模型预测[J].化工学报,2017,68(3):1049-1057.
[11]陈志刚,梁涤青,邓小鸿,等.Logistic混沌映射性能分析与改进[J].电子与信息学报,2016,38(6):1547-1551.