Table 35 Statistical results of optimization algorithms in the gear train design problem.
From: Learning cooking algorithm for solving global optimization problems
\({\text {Algorithms}}\) | \({\text {Mean}}\) | \({\text {Std}}\) | \({\text {Minimum}}\) | \({\text {Maximum}}\) | \({\text {Median}}\) |
|---|---|---|---|---|---|
LCA | 5.670E–37 | 8.886E–37 | 0.000E+00 | 1.890E–36 | 0.000E+00 |
TSA | 4.218E–12 | 6.905E–12 | 1.196E–14 | 2.871E–11 | 1.140E–12 |
SSA | 1.268E–02 | 2.703E–02 | 4.163E–06 | 9.163E–02 | 1.420E–03 |
MVO | 2.579E–13 | 4.637E–13 | 1.320E–16 | 1.626E–12 | 2.829E–14 |
SCA | 2.396E–10 | 3.358E–10 | 1.881E–12 | 1.257E–09 | 9.631E–11 |
GWO | 1.184E–12 | 2.826E–12 | 2.113E–16 | 1.240E–11 | 2.005E–13 |
WOA | 1.110E–20 | 4.965E–20 | 0.000E+00 | 2.220E–19 | 0.000E+00 |
GJO | 2.547E–12 | 3.648E–12 | 4.165E–14 | 1.575E–11 | 7.313E–13 |
IGWO | 1.134E–12 | 2.367E–12 | 1.322E–15 | 1.025E–11 | 1.671E–13 |
MWOA | 1.002E–33 | 4.301E–33 | 0.000E+00 | 1.926E–32 | 0.000E+00 |
MTBO | 1.793E–12 | 3.475E–12 | 1.366E–15 | 1.400E–11 | 2.271E–13 |
BWO | 1.728E–11 | 3.593E–11 | 8.147E–16 | 1.561E–10 | 6.227E–12 |
MGO | 1.064E–14 | 4.462E–14 | 0.000E+00 | 2.001E–13 | 8.414E–17 |
SCSO | 3.212E–14 | 4.096E–14 | 1.554E–16 | 1.485E–13 | 1.457E–14 |
