Nonlinear Harris Hawk Optimization Algorithm Based on Sine and Cosine
XIA Xiaogang
PENG Jiachao
Abstract：Aiming at the problems of low convergence accuracy and easy to fall into local optimization of Harris hawk optimization(HHO)algorithm,a nonlinear Harris hawk optimization(SCNHHO)algorithm based on sine-cosine is proposed.Firstly,a good point set strategy is adopted to initialize the population,so as to make the population distribution more uniform and improve the convergence speed and accuracy of the algorithm;secondly,a positive cosine strategy is introduced in the exploration stage,which makes use of the oscillatory property of the positive cosine function to expand the search range and seek for more potential high-quality solutions;and lastly,a nonlinear parameter is introduced in the exploitation stage to balance the exploration and exploitation,so as to prevent the algorithm from falling into the local optimum.Performance tests are conducted for benchmark test functions of different dimensions,and the algorithm is analyzed with five other comparison algorithms by combining the results of Wilcoxon rank sum test and Friedman test.The results show that the performance of the improved algorithm is greatly improved over the original HHO algorithm,and it outperforms the zebra optimization algorithm(ZOA),the whale optimization algorithm(WOA),and the two variations of the Harris hawk algorithm(MHHO and IHHO),which verifies the effectiveness of the improved strategy.Finally,the practicality of SCNHHO is further verified by a three-bar truss design problem.
Keywords：Harris hawk optimization algorithmgood point set strategysine-cosine functionnonlinear parametersWilcoxon rank sum testbenchmarking function
Publication Date：2024-10-25
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：12( 93-104 )