Grey Wolf Optimizer Based on Powell Local Optimization Method for Clustering Analysis

Table 2

Initial parameters of algorithms.

Algorithm	Parameter	Value
PGWO	Population size	30
		Linearly decreased from 2 to 0
	Performing probability of Powell ()	0.5
	Max iteration	500 (benchmark functions test), 200 (data sets test)
	Stopping criteria	Max iteration
GWO	Population size	30
		Linearly decreased from 2 to 0
	Max iteration	500 (functions test), 200 (data sets test)
	Stopping criteria	Max iteration
PSO	Population size	30
		1.4962, 1.4962
		0.7298
	Max iteration	500 (benchmark functions test), 200 (data sets test)
	Stopping criteria	Max iteration
ABC	Population size	30
	Limit	10
	Max iteration	500 (benchmark functions test), 200 (data sets test)
	Stopping criteria	Max iteration
CS	Population size	30
		0.25
	Max iteration	500 (benchmark functions test), 200 (data sets test)
	Stopping criteria	Max iteration
GGSA	Population size	30
		1
		20
	Max iteration	500 (benchmark functions test), 200 (data sets test)
	Stopping criteria	Max iteration

indicates the maximum number of interactions; is the current iteration.