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Table 2 Parameter setting of compared and proposed algorithms for UBFs

From: An advanced hybrid meta-heuristic algorithm for solving small- and large-scale engineering design optimization problems

Algorithm

Year

References

Control parameter

Population size

Stopping criterion

Run

Term

Values

EO

2019

[12]

a1, a2 and GP

{1, 1.5, 2, 2.5, 3}, {0.1, 0.5, 1, 1.5, 2} and (0.1.0.25, 0.5, 0.75, 0.9}

30

500

30

HHO

2019

[5]

Escaping energy

\(E<0.5, E\ge 0.5\)

30

500

30

JADE

2009

[17]

Fi and CRi,

randciF, 0.1) and randniCR, 0.1)

50

1000

30

SHADE

2013

[18]

Pbest and Arc rate

0.1 and 2

30

500

30

HEPSO

2014

[22]

PC and PB

0.95 and 0.02

50

500

30

RPSOLF

2017

[23]

w, c1, c2, c3 and β, ε

0.55, 1.49, 1.49, 1.5 and 0.99

50

500

30

FAPSO

2018

[34]

50

5000

30

PSOSCALF

2018

[35]

wmin, wmax, c1min, c1max, c2min, c2max and β

0.4, 0.9, 0.5, 2.5, 0.5, 2.5 and 1.5

50

500

30

aDE

Proposed

 

30

500

30

aPSO

  

\({w}_{i}, {w}_{f}, {c}_{1i}, {c}_{1f}, {c}_{2i}\) and \({c}_{2f}\)

0.4, 0.9, 0.5, 2.5, 2.5 and 0.5

30

500

30

haDEPSO

  

30

500

30