Table 30 The comparison results of the welded beam design problem.
From: Learning cooking algorithm for solving global optimization problems
Algorithms | Optimal values for variables | Optimum weight | |||
|---|---|---|---|---|---|
h | l | t | b | ||
LCA | 1.922E–01 | 6.087E+00 | 9.008E+00 | 2.087E–01 | 1.715E+00 |
TSA | 1.953E–01 | 3.776E+00 | 8.992E+00 | 2.082E–01 | 1.760E+00 |
SSA | 4.527E–01 | 1.820E+00 | 1.801E+00 | 1.494E+00 | 6.137E+24 |
MVO | 2.031E–01 | 3.446E+00 | 9.266E+00 | 2.046E–01 | 1.748E+00 |
SCA | 1.875E–01 | 4.230E+00 | 8.807E+00 | 2.210E–01 | 1.872E+00 |
GWO | 2.056E–01 | 3.477E+00 | 9.040E+00 | 2.057E–01 | 1.726E+00 |
WOA | 1.779E–01 | 6.451E+00 | 8.464E+00 | 2.345E–01 | 2.179E+00 |
GJO | 2.000E–01 | 3.599E+00 | 9.038E+00 | 2.059E–01 | 1.734E+00 |
IGWO | 2.057E–01 | 3.472E+00 | 9.037E+00 | 2.057E–01 | 1.725E+00 |
MWOA | 2.391E–01 | 3.080E+00 | 8.411E+00 | 2.392E–01 | 1.848E+00 |
MTBO | 2.057E–01 | 3.470E+00 | 9.037E+00 | 2.057E–01 | 1.725E+00 |
BWO | 1.490E–01 | 5.884E+00 | 9.085E+00 | 2.081E–01 | 1.952E+00 |
HHO | 1.835E–01 | 4.461E+00 | 8.816E+00 | 2.162E–01 | 1.858E+00 |
MGO | 1.872E–01 | 3.691E+00 | 9.590E+00 | 2.031E–01 | 1.801E+00 |
SCSO | 1.927E–01 | 3.777E+00 | 9.037E+00 | 2.058E–01 | 1.745E+00 |
