| | 1 | = SGA TSP = |
| | 2 | == Description == |
| | 3 | An SGA with 1-elitism applied on the ch130 TSP problem. |
| | 4 | |
| | 5 | == Parameters == |
| | 6 | * Population Size = 100 |
| | 7 | * Mutation Rate = 5% |
| | 8 | * Maximum Generations = 1000 |
| | 9 | * Elites = 1 |
| | 10 | * Parents = 200 |
| | 11 | |
| | 12 | == Implementation & Notes == |
| | 13 | Works with revision r3. |
| | 14 | |
| | 15 | == Results & Conclusions == |
| | 16 | After 1000 generations on average a best solution quality of about 60% away from the global optimum is reached. |
| | 17 | |
| | 18 | This example is very classical. It should demonstrate how a simple SGA can be realized in HeuristicLab 3.0. It is for sure not a good example of a very performant GA. |
| | 19 | |
| | 20 | ---- |
