Research Article
Evolutionary Computation with Spatial Receding Horizon Control to Minimize Network Coding Resources
Table 3
Details of the results of the new GlobalGAs.
| | (Average results of 20 runs) | Case I-1 | Case I-2 | Case II-1 | Case II-2 | Case II-3 | Case II-4 |
| | Final max fitness | | | | | | | | GlobalGA1 | 149.65 | 190.00 | 240.00 | 230.00 | 181.67 | 40.21 | | GlobalGA2 | 171.54 | 195.66 | 240.00 | 240.00 | 195.64 | 59.09 | | GlobalGA3 | 280.00 | 260.00 | 240.00 | 240.00 | 240.00 | 240.00 |
| | How many generations to achieve final max fitness | | | | | | | | GlobalGA1 | 245.50 | 239.60 | 2.35 | 9.40 | 242.40 | 300.00 | | GlobalGA2 | 210.75 | 221.00 | 1.05 | 5.80 | 171.90 | 300.00 | | GlobalGA3 | 64.40 | 39.10 | 1.00 | 2.20 | 11.45 | 56.70 |
| | Average minimal coding links | | | | | | | | GlobalGA1 | 1.20 | 0.80 | 0.00 | 0.00 | 0.80 | 6.30 | | GlobalGA2 | 1.15 | 0.70 | 0.00 | 0.00 | 0.30 | 5.00 | | GlobalGA3 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| Maximum minimal
coding links | | | | | | | | GlobalGA1 | 4 | 3 | 0 | 1 | 3 | 22 | | GlobalGA2 | 3 | 1 | 0 | 0 | 2 | 12 | | GlobalGA3 | 0 | 0 | 0 | 0 | 0 | 0 |
| Minimum actually achieved rate
at sinks | | | | | | | | GlobalGA1 | 3 | 3 | 2 | 2 | 1 | 1 | | GlobalGA2 | 3 | 3 | 2 | 2 | 2 | 1 | | GlobalGA3 | 4 | 3 | 2 | 2 | 2 | 2 |
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