Table 1 The values of parameters used for multi-objective optimization by G.A. approaches.
From: Intelligent modeling and optimization of titanium surface etching for dental implant application
Optimization parameter | Value |
|---|---|
Initial population size | 25 |
Crossover mechanism | Arithmetic |
Crossover rate | 70% |
Mutation mechanism | Polynomial |
Mutation rate | 40% |
Selection mechanism | Ternary tournament selection |
Maximum iteration number | 50 |
