Table 5 Parameter settings for different optimization algorithms.
Algorithm | Parameters |
|---|---|
GA | Population size (10) |
Generations (50) | |
Crossover probability (0.8) | |
Mutation probability (0.2) | |
Convergence threshold (1 × 10−5) | |
PSO | Number of particles (10) |
Iterations (50) | |
Inertia weight (0.5) | |
Cognitive/social coefficients (c1 = 1.5, c2 = 1.5) | |
Convergence threshold (1 × 10−5) | |
WOA | Number of agents (20) |
Iterations (50) | |
Search range control (a: 2 → 0) | |
Search probability weight (a2: − 1 → 0) | |
Stochastic learning probability (0.1), switch probability (0.5) | |
Convergence threshold (1 × 10−5) |
