Improved hybrid Jaya Grey Wolf optimization algorithm
Chuxin Wang, Zhiyuan Hu, Yunfeng Chen, Yuanjie Tang · 2022
The grey wolf optimization algorithm is a competitive optimization technique, however, it has the disadvantage of low precision and slow convergence. Aiming at the above shortcomings, inspired by Jaya algorithm, an improved grey wolf algorithm is proposed. The novel algorithm introduces the worst position of the best wolf pack and the individual historical best position into the original position update equation. The simulation results of nine classical test functions show that compared with other standard algorithms, the hybrid grey wolf optimization algorithm has advantages in both convergence speed and solution accuracy in most cases.