Junqiang Jiang1,2, Zhifang Sun1, Xiong Jiang1, Shengjie Jin1, Yinli Jiang3, Bo Fan1,*
CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1617-1644, 2023, DOI:10.32604/cmc.2023.041973
Abstract The grey wolf optimizer (GWO) is a swarm-based intelligence optimization algorithm by simulating the steps
of searching, encircling, and attacking prey in the process of wolf hunting. Along with its advantages of simple
principle and few parameters setting, GWO bears drawbacks such as low solution accuracy and slow convergence
speed. A few recent advanced GWOs are proposed to try to overcome these disadvantages. However, they are
either difficult to apply to large-scale problems due to high time complexity or easily lead to early convergence. To
solve the abovementioned issues, a high-accuracy variable grey wolf optimizer (VGWO) with low time complexity… More >
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