Table 26 The comparison results of the tension/compression spring design problem.
From: Learning cooking algorithm for solving global optimization problems
Algorithms | Optimal values for variables | Optimum weight | ||
|---|---|---|---|---|
\({\text {d}}\) | \({\text {D}}\) | \({\text {N}}\) | ||
LCA | 5.566E–02 | 4.591E–01 | 7.194E+00 | 1.250E–02 |
TSA | 5.446E–02 | 4.256E–01 | 8.221E+00 | 1.290E–02 |
SSA | 6.779E–02 | 1.039E+00 | 1.240E+00 | 3.231E+13 |
MVO | 6.903E–02 | 9.348E–01 | 2.000E+00 | 1.782E–02 |
SCA | 5.548E–02 | 4.536E–01 | 7.311E+00 | 1.300E–02 |
GWO | 5.419E–02 | 4.197E–01 | 8.379E+00 | 1.279E–02 |
WOA | 5.714E–02 | 5.025E–01 | 6.030E+00 | 1.317E–02 |
GJO | 5.702E–02 | 4.984E–01 | 6.133E+00 | 1.318E–02 |
IGWO | 5.118E–02 | 3.444E–01 | 1.206E+01 | 1.268E–02 |
MWOA | 5.859E–02 | 5.467E–01 | 5.179E+00 | 1.347E–02 |
MTBO | 5.327E–02 | 3.958E–01 | 9.328E+00 | 1.273E–02 |
BWO | 5.000E–02 | 3.119E–01 | 1.500E+01 | 1.326E–02 |
HHO | 6.223E–02 | 6.672E–01 | 3.624E+00 | 1.453E–02 |
MGO | 5.000E–02 | 3.104E–01 | 1.500E+01 | 1.319E–02 |
SCSO | 5.833E–02 | 5.385E–01 | 5.322E+00 | 1.342E–02 |
