Research Article
Fusion Global-Local-Topology Particle Swarm Optimization for Global Optimization Problems
Table 2
Minimization results for the unimodal and multimodal functions (maximum iteration = 5000 and
).
| Function | FGLT-PSO | PSO | LPSO | QIPSO |
| | Avg. best solution | 0.000e + 000 | 1.405e − 135 | 1.452e − 063 | 1.526e − 138 | SD | 0.000e + 000 | 6.789e − 135 | 5.681e − 063 | 5.723e − 138 | Median best solution | 0.000e + 000 | 1.243e − 139 | 7.381e − 065 | 3.961e − 142 | Avg. iteration for finding the best solution | 2646 | 5000 | 5000 | 5000 |
| | Avg. best solution | 2.741e − 273 | 2.992e − 077 | 4.130e − 038 | 6.663e − 079 | SD | 0.000e + 000 | 1.490e − 076 | 7.564e − 038 | 1.234e − 078 | Median best solution | 6.578e − 277 | 3.849e − 079 | 9.945e − 039 | 1.019e − 079 | Avg. iteration for finding the best solution | 4952 | 5000 | 4999 | 5000 |
| | Avg. best solution | 1.637e − 116 | 3.215e − 044 | 5.110e − 014 | 3.919e − 044 | SD | 8.969e − 116 | 1.565e − 043 | 1.126e − 013 | 2.117e − 043 | Median best solution | 2.369e − 127 | 1.857e − 048 | 5.320e − 015 | 3.570e − 048 | Avg. iteration for finding the best solution | 4630 | 4999 | 4999 | 4999 |
| | Avg. best solution | 3.209e − 004 | 4.738e − 004 | 1.269e − 003 | 6.514e − 004 | SD | 3.006e − 004 | 2.057e − 004 | 4.861e − 004 | 3.241e − 004 | Median best solution | 2.114e − 004 | 4.595e − 004 | 1.197e − 003 | 5.797e − 004 | Avg. iteration for finding the best solution | 3715 | 4404 | 4414 | 4459 |
| | Avg. best solution | 2.973e − 001 | 1.820e + 000 | 1.661e + 000 | 2.040e + 000 | SD | 1.015e + 000 | 1.336e + 000 | 1.281e + 000 | 1.622e + 000 | Median best solution | 4.614e − 004 | 2.014e + 000 | 1.727e + 000 | 1.862e + 000 | Avg. iteration for finding the best solution | 4537 | 4811 | 4988 | 4837 |
| | Avg. best solution | −3.910e + 003 | −3.452e + 003 | −3.892e + 003 | −3.424e + 003 | SD | 1.184e + 002 | 2.307e + 002 | 1.843e + 002 | 2.775e + 002 | Median best solution | −3.953e + 003 | −3.475e + 003 | −3.834e + 003 | −3.475e + 003 | Avg. iteration for finding the best solution | 2974 | 2726 | 3918 | 2635 |
| | Avg. best solution | 4.441e − 015 | 4.322e − 015 | 4.441e − 015 | 4.441e − 015 | SD | 0.000e + 000 | 6.486e − 016 | 0.000e + 000 | 0.000e + 000 | Median best solution | 4.441e − 015 | 4.441e − 015 | 4.441e − 015 | 4.441e − 015 | Avg. iteration for finding the best solution | 376 | 3147 | 3772 | 3109 |
| | Avg. best solution | 4.712e − 032 | 4.712e − 032 | 4.712e − 032 | 4.712e − 032 | SD | 1.670e − 047 | 1.670e − 047 | 1.670e − 047 | 1.670e − 047 | Median best solution | 4.712e − 032 | 4.712e − 032 | 4.712e − 032 | 4.712e − 032 | Avg. iteration for finding the best solution | 420 | 3166 | 3895 | 2687 |
| | Avg. best solution | 9.495e − 002 | 9.667e − 001 | 1.574e + 000 | 0.000e + 000 | SD | 2.720e − 001 | 4.560e + 000 | 1.065e + 000 | 0.000e + 000 | Median best solution | 9.236e − 008 | 0.000e + 000 | 2.000e + 000 | 0.000e + 000 | Avg. iteration for finding the best solution | 4856 | 3357 | 4366 | 3401 |
| Avg. rank | 1.1 | 2.9 | 3.4 | 2.6 | Final rank | 1 | 3 | 4 | 2 | Algorithms | FGLT-PSO | PSO | LPSO | QIPSO |
|
|