TABLE 4.
The results of optimization process via different evolutionary optimization algorithms (BBO, SOS, ISA, and GA).
| Fitness function | Optimization algorithm | Optimal level of input variables |
Predicted fitness function value | ||||
| Blue (μmol/m2/s) | Red (μmol/m2/s) | White (μmol/m2/s) | Far-red (μmol/m2/s) | Sucrose (%) | |||
| Shoot length (mm) | BBO | 15.412 | 9.412 | 15.997 | 43.271 | 3.142 | 160.78 |
| SOS | 4.460 | 19.051 | 27.337 | 39.472 | 3.157 | 160.78 | |
| ISA | 0.439 | 18.494 | 36.234 | 33.122 | 3.319 | 160.78 | |
| GA | 2.937 | 0.270 | 13.036 | 30.605 | 3.505 | 160.78 | |
| Root length (mm) | BBO | 5.756 | 87.381 | 31.523 | 19.343 | 3.504 | 262.21 |
| SOS | 0.508 | 79.897 | 4.733 | 17.209 | 3.673 | 262.21 | |
| ISA | 3.779 | 81.519 | 25.386 | 13.321 | 3.634 | 262.21 | |
| GA | 5.797 | 98.198 | 36.208 | 1.237 | 3.507 | 262.21 | |
| Node number | BBO | 62.998 | 92.238 | 48.520 | 8.830 | 3.709 | 12.25 |
| SOS | 57.682 | 87.192 | 45.468 | 19.924 | 3.711 | 12.25 | |
| ISA | 46.845 | 90.135 | 20.969 | 16.824 | 3.220 | 12.25 | |
| GA | 50.960 | 88.355 | 11.000 | 11.673 | 3.709 | 12.25 | |
| Shoot number | BBO | 16.581 | 36.686 | 0.592 | 19.995 | 2.909 | 3.75 |
| SOS | 15.930 | 21.183 | 9.723 | 24.304 | 2.372 | 3.75 | |
| ISA | 21.336 | 29.584 | 0.332 | 17.387 | 2.174 | 3.75 | |
| GA | 25.303 | 25.471 | 0.262 | 18.125 | 3.160 | 3.75 | |
| Canopy surface area (mm2) | BBO | 52.563 | 84.052 | 26.262 | 22.456 | 3.809 | 7168.05 |
| SOS | 54.688 | 95.974 | 30.099 | 24.543 | 3.664 | 7168.05 | |
| ISA | 44.889 | 99.642 | 49.994 | 24.674 | 3.285 | 7168.05 | |
| GA | 37.646 | 83.928 | 17.507 | 1.811 | 3.083 | 7168.05 | |
BBO, biogeography-based optimization; GA, genetic algorithm; ISA, interior search algorithm; SOS, symbiotic organisms search.