Improved Grey Wolf Optimization Algorithm Based on Antisine Inertial Weights
Yingling Chen, Zhongliang Pan · 2023
An improved Grey Wolf optimization algorithm (AGWO) based on antisine function inertia weight was proposed to solve the problems of slow convergence and local optimum in the optimization of Grey Wolf optimization algorithm (GWO). AGWO improved the optimization performance of GWO by using the nonlinear inertia weight strategy based on arcsine function. Five classical test functions were used to verify the optimization performance of AGWO. The experimental results show that AGWO has better convergence speed, stability and optimization accuracy than other five typical swarm intelligence algorithms.