Table 1.
Parameter | Parameter setting |
---|---|
Algorithm | NSGAII [15] |
Population size | 300 |
Elite size | 30 |
Generations | 1500 |
Crossover | subtreea |
Crossover probability | 0.9 |
Mutation | subtreea |
Mutation events | 1 |
Selection proportion | 0.5 |
Fitness 1 | F1 |
Fitness 2 | Minimizing the number of nodes |
Maximum derivation tree initialization depth | 10 |
Maximum derivation tree depth | 15 |
Initialization strategy | PI grow [21] |
a The crossover strategy is analogous to the one-point operator but by mixing tree structures. The mutation operator is applied only to the population resulting from the crossover