Improved Catfish Effect Grey Wolf Optimization Algorithm Based on Double Weight Factor
LIU Cheng-han,HE Qing,DU Ni-suo,CHEN Jun
1(School of Big Data and Information Engineering,Guizhou University,Guiyang 550025,China)2(Guizhou Provincial Key Laboratory of Public Big Data,Guiyang 550025,China)
Abstract：An improved catfish effect Grey Wolf optimization algorithm(IGWO)based on double weight factor was proposed to solve the problems of premature convergence,low searching speed and low precision of GWO algorithm.Firstly,Logistic chaotic map was used to initialize grey Wolf population to improve the quality of initial location of population.Then two different weighting factors are introduced for headwolf disturbance and individual search step size to balance local development and global search capability.Finally,an improved catfish effect strategy is added to ensure population vitality,further improve the convergence accuracy of the algorithm,and avoid the algorithm falling into the local optimal solution.The simulation results show that the improved grey Wolf optimization algorithm has high robustness by using 10 standard test functions to compare with other intelligent optimization algorithms for low and high dimensions,and comparing with other improved grey Wolf optimization algorithms.
2022, Vol. 43 
