Table 19.
Best normalized optimization results and average CPU time on UCAV path planning problem on different ε. The numbers shown are the best results found after 100 Monte Carlo simulations of BAM algorithm.
| Parameter | Algorithm | ||||
|---|---|---|---|---|---|
| F | ε | BAM | |||
| Best | Worst | Mean | CPU Time (sec) | ||
| 0.5 | 0 | 0.8817 | 12.3484 | 2.9293 | 9.08 |
| 0.5 | 0.1 | 0.4541 | 3.4890 | 0.7290 | 9.84 |
| 1.0 | 0.2 | 0.4860 | 6.7479 | 0.9062 | 9.77 |
| 0.5 | 0.3 | 0.5158 | 7.8852 | 1.0775 | 9.76 |
| 0.5 | 0.4 | 0.5580 | 7.9747 | 1.0161 | 9.76 |
| 0.5 | 0.5 | 0.5570 | 8.6947 | 1.4135 | 9.67 |
| 0.5 | 0.6 | 0.6282 | 10.1393 | 1.3083 | 9.80 |
| 0.5 | 0.7 | 0.6363 | 10.8901 | 1.2981 | 9.82 |
| 0.5 | 0.8 | 0.6442 | 7.6385 | 1.5515 | 9.74 |
| 0.5 | 0.9 | 0.6779 | 9.9564 | 1.8094 | 9.68 |
| 0.5 | 1.0 | 0.7060 | 9.5250 | 1.9116 | 9.61 |