Table 3 Parameter settings for used meta-heuristic optimization algorithms

All algorithms

Run’s number \(=30\)

Iterations number \(G_{max}=100\)

Size of population \(N=10\)

Dimensionality d = The number of attributes in the used benchmark

BAVO

Parameter \(L_1=0.7\)

Parameter \(L_2=0.2\)

Parameter \(w=2\)

Parameter \(P_1=0.6\)

Parameter \(P_2=0.6\)

Parameter \(P_3=0.5\)

BAO

Number of search rotations \({\mathfrak {r}}_{1}=10\)

\(U = 0.00565\)

\(\omega = 0.005\)

Adjustment parameters for exploitation stage \(\alpha =0.1\) and \(\delta =0.1\)

Aquila’s arbitrary motions \({\mathcal {Q}_1} \in [-1,1]\)

Aquila’s flying slope \({\mathcal {Q}_2} \in [2,0]\)

BSSA

Number of scroungers \(SD=0.1 ^*N\)

Number of producers \(PD=0.2 ^*N\)

Safety threshold \(ST=0.8\)

BASO

Multiplier weight \(\beta =0.2\)

Depth weight \(\alpha =50\)

BHGSO

Number of clusters \(=2\)

\(l_1=5E-03\), \(l_2=1E+02\), and \(l_3=1E-02\)

\(\alpha =\beta =0.1\) and \(K=1\)

BHHO

Rabbit energy \(E \in [-1,1]\)

BSFO

Ratio between sardines and sailfish \(pp=0.1\)

\(\varepsilon =0.0001\)

\(A=1\)

BBA

Loudness \(A=0.8\)

Lower and upper pulse frequencies \(={0,10}\)

Pulse emission rate \(r=0.95\)

BGOA

\(C_\text{min}=0.00004\) and \(C_\text{max}=1\)

BABC

Number of employed bees \(=16\)

Number of scout bees \(=3\)

Number of onlooker bees \(=4\)

BPSO

Inertia weight \(\omega _{max}=0.9, \omega _{min}=0.4\)

Acceleration coefficients \(\left( c_2=c_1=1.2 \right)\)