Table 34 Gear train design comparison results.
From: Learning cooking algorithm for solving global optimization problems
Algorithms | Optimal values for variables | Optimum weight | |||
|---|---|---|---|---|---|
\(z_{1}\) | \(z_{2}\) | \(z_{3}\) | \(z_{4}\) | ||
LCA | 5.593E+01 | 1.435E+01 | 3.146E+01 | 5.593E+01 | 0.000E+00 |
TSA | 5.535E+01 | 2.621E+01 | 1.723E+01 | 5.657E+01 | 9.901E–14 |
SSA | 1.462E+01 | 2.251E+01 | 1.656E+01 | 5.790E+01 | 8.772E–02 |
MVO | 4.592E+01 | 3.163E+01 | 1.257E+01 | 6.000E+01 | 8.957E–13 |
SCA | 5.772E+01 | 1.203E+01 | 1.419E+01 | 2.049E+01 | 8.291E–10 |
GWO | 5.037E+01 | 2.648E+01 | 1.434E+01 | 5.227E+01 | 1.240E–11 |
WOA | 5.503E+01 | 3.185E+01 | 1.364E+01 | 5.470E+01 | 0.000E+00 |
GJO | 5.778E+01 | 3.096E+01 | 1.200E+01 | 4.456E+01 | 5.081E–12 |
IGWO | 5.468E+01 | 1.369E+01 | 2.879E+01 | 4.998E+01 | 8.180E–13 |
MWOA | 5.546E+01 | 1.252E+01 | 1.995E+01 | 3.122E+01 | 0.000E+00 |
MTBO | 5.906E+01 | 1.228E+01 | 3.253E+01 | 4.689E+01 | 1.360E–14 |
BWO | 6.000E+01 | 4.328E+01 | 1.200E+01 | 6.000E+01 | 6.305E–12 |
MGO | 5.308E+01 | 2.214E+01 | 1.371E+01 | 3.965E+01 | 7.861E–18 |
SCSO | 2.829E+01 | 1.258E+01 | 1.200E+01 | 3.700E+01 | 1.112E–14 |
