Table 2. Algorithms parameters and values.
| SHO | ACO | PSO | CS | ||||
|---|---|---|---|---|---|---|---|
| Number of populations | 50 | Number of populations | 50 | Number of populations | 100 | Number of populations | 50 |
| Maximum iterations | 500 | Maximum iterations | 500 | Maximum iterations | 500 | Maximum iterations | 500 |
| Dimension | 5 | Phromone exponential weight | −1 | Inertia weight | −1 | Dimension | 5 |
| Lower boundary | −1 | Heuristic exponential weight | 1 | Inertia weight damping ratio | 0.99 | Lower bound and upper bound | −1 and 1 |
| Upper boundary | 1 | Evaporation rate | 1 | Personal and global learning coefficient | 1.5 and 2 | Number of nests | 20 |
| Prey’s rate | 0.7, 0.9 | Lower bound and upper bound | −1 and 1 | Lower bound and upper bound | −10 and 10 | Transition probability coefficient | 0.1 |
| Number of runs | 100 | Number of runs | 100 | Number of runs | 100 | Number of runs | 100 |