Research Article
An Adaptive Evolutionary Algorithm for Traveling Salesman Problem with Precedence Constraints
Table 2
The performance experiment result 1.
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Number of nodes | Parameter | General approach | AEA* | | pc0 | Best solution | Frequency of best | CPU Time (sec) | Best solution | Frequency of best
| CPU time (sec) |
| 7 | 7 14 | 0.6 0.7 | 26 26 | 6 3 | 0.922 0.015 | 26 26 | 1 4 | 0.006 0.016 |
| 25 | 25 50 | 0.6 0.7 | 134 134 | 10 5 | 10.422 6.042 | 134 134 | 4 5 | 0.047 0.094 |
| 35 | 30 35 70 | 0.6 0.7 0.8 | 177 180 180 | 11 12 11 | 18.803 23.844 19.424 | 177 177 177 | 9 10 16 | 0.218 0.235 0.625 |
| 45 | 45 45 50 | 0.6 0.7 0.8 | 214 214 209 | 15 17 18 | 44.314 38.688 42.124 | 209 207 207 | 18 19 17 | 1.047 1.75 1.547 |
| 70 | 70 70 140 | 0.6 0.7 0.8 | 383 372 372 | 33 21 27 | 532.406 229.319 245.247 | 363 363 363 | 43 40 45 | 9.016 9.796 14.281 |
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The proposed adaptive evolutionary algorithm.
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