A Versatile Genetic Algorithm System in Ada: Implementation and Applications
Max Edwards
See VAGAS/ttbl_ga/main.A
See VAGAS/dejong_ga/main.A
See VAGAS/meta_tsp_ga/main.A
The following parameters were used for all the meta-runs:
Bits per parameter | 6 |
Maximum application fitness evaluations per run | 2000 |
Maximum application generations per run | 500 |
Crossover method | Simple |
Mutation method | Simple |
Selection method | Roulette |
Scaling method | Simple Linear |
The following parameters were used for the individual meta-runs:
Run | Pop. size | Num. gens. | Xover rate | Mut. rate | GA runs/eval. | Measure |
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1 | 128 | 128 | 0.75 | 0.05 | 1 | off-line |
2 | 256 | 512 | 0.75 | 0.05 | 1 | off-line |
3 | 256 | 64 | 0.75 | 0.05 | 3 | off-line |
4 | 128 | 128 | 0.75 | 0.05 | 5 | off-line |
5 | 128 | 128 | 0.75 | 0.05 | 8 | off-line |
6 | 128 | 250 | 0.85 | 0.02 | 8 | off-line |
7 | 128 | 250 | 0.85 | 0.02 | 16 | on-line |
8 | 256 | 127 | 0.9 | 0.02 | 16 | on-line |
9 | 128 | 128 | 0.85 | 0.02 | 16 | on-line |