Table 38 Cantilever beam comparison results.
From: Learning cooking algorithm for solving global optimization problems
Algorithms | Optimal values for variables | Optimum weight | ||||
|---|---|---|---|---|---|---|
\(z_{1}\) | \(z_{2}\) | \(z_{3}\) | \(z_{4}\) | \(z_{5}\) | ||
LCA | 5.627E+00 | 5.392E+00 | 4.439E+00 | 3.433E+00 | 3.204E+00 | 1.3289 |
TSA | 6.070E+00 | 5.335E+00 | 4.420E+00 | 3.552E+00 | 2.129E+00 | 1.3419 |
SSA | 1.116E+01 | 3.392E+01 | 1.373E+01 | 5.215E+01 | 9.018E+00 | 7.4865 |
MVO | 5.951E+00 | 5.432E+00 | 4.589E+00 | 3.453E+00 | 2.069E+00 | 1.3412 |
SCA | 5.531E+00 | 4.942E+00 | 4.841E+00 | 3.842E+00 | 3.101E+00 | 1.3888 |
GWO | 5.998E+00 | 5.315E+00 | 4.483E+00 | 3.503E+00 | 2.175E+00 | 1.3400 |
WOA | 4.660E+00 | 1.078E+01 | 5.578E+00 | 3.112E+00 | 3.376E+00 | 1.7160 |
GJO | 5.975E+00 | 5.320E+00 | 4.463E+00 | 3.542E+00 | 2.177E+00 | 1.3401 |
IGWO | 6.016E+00 | 5.331E+00 | 4.481E+00 | 3.488E+00 | 2.158E+00 | 1.3399 |
MWOA | 6.616E+00 | 4.950E+00 | 5.635E+00 | 3.890E+00 | 1.568E+00 | 1.4139 |
MTBO | 6.022E+00 | 5.306E+00 | 4.495E+00 | 3.495E+00 | 2.156E+00 | 1.3399 |
BWO | 5.853E+00 | 5.425E+00 | 4.707E+00 | 3.252E+00 | 2.383E+00 | 1.3491 |
HHO | 5.870E+00 | 5.187E+00 | 4.596E+00 | 3.649E+00 | 2.202E+00 | 1.3419 |
MGO | 6.001E+00 | 5.286E+00 | 4.509E+00 | 3.525E+00 | 2.153E+00 | 1.3399 |
SCSO | 6.061E+00 | 5.279E+00 | 4.455E+00 | 3.518E+00 | 2.162E+00 | 1.3400 |
