Table 2.

Parameter values for the comparative algorithms.

Algorithm	Parameter	Value
GA
	Type	Real coded
	Selection	Roulette wheel (proportionate)
	Crossover	Whole arithmetic (probability = 0.8, $\alpha \in \left[-0.5, 1.5\right]$)
	Mutation	Gaussian (probability = 0.05)
PSO
	Topology	Fully connected
	Cognitive and social constant	$C_1=2,C_2=2$
	Inertia weight	Linear reduction from 0.9 to 0.1
	Velocity limit	10% of dimension range
GSA
	Alpha, $G_0$, $R_{norm}$, $R_{power}$	20, 100, 2, 1
TLBO
	$T_F$: teaching factor	$T_F=$ round $\left[\left(1+rand\right)\right]$
	Random number	rand is a random number in $\left[0, 1\right].$
GWO
	Convergence parameter (a)	a: Linear reduction from 2 to 0.
WOA
	Convergence parameter (a)	a: Linear reduction from 2 to 0.
	r is a random vector in $\left[0, 1\right].$
	l is a random number in $\left[-1, 1\right].$
TSA
	$P_{min}$ and $P_{max}$	1, 4
	$c_1,c_2,c_3$	Random numbers lie in the range of $\left[0–1\right].$
MPA
	Constant number	P = 0.5
	Random vector	R is a vector of uniform random numbers in $\left[0, 1\right].$
	Fish Aggregating Devices (FADs)	FADs = 0.2
	Binary vector	U = 0 or 1