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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