Dimensional Learning Strategy-Based Grey Wolf Optimizer for Solving the Global Optimization Problem

Table 4

Parameter settings and explanations for all versions of the GWO.

Name	Explanation	Parameters
GWO		= [2,0]
RWGWO [39]	GWO with random walk	= [2,0]
learnGWO [50]	GWO with improved hierarchy	= [2,0],  = 0.004715,  =  = 0.00647
GWOCS [44]	GWO hybridized with cuckoo search	= [2,0]
IGWO [56]	GWO with individual memory	= [2,0],  = 0.6,  = 0.4,  = 0.5
SOGWO [43]	GWO with opposition-based learning	= [2,0]
MGWO [34]	GWO with modified parameter C	= [2,0]