Table 4 Parameter structures of the employed algorithms in the study.
Algorithm | Parameter | Value |
|---|---|---|
Artificial Electric Field Algorithm (AEFA) [38] | Quantity of candidates | 200 |
Search space | 20 | |
Factor of compass and map | 0.2 | |
Operation limit of compass and map | 150 | |
Operation limit of Landmark | 200 | |
Inertia factor (\(\:w\)) | 1 | |
Factor of self-confidence (\(\:{c}_{1}\)) | 1.2 | |
Factor of Swarm confidence (\(\:{c}_{2}\)) | 1.2 | |
Harris Hawks Optimization (HHO) [39] | Max Iteration | 200 |
Size of market | 40 | |
FunIndex | 1 | |
White Shark Optimizer (WSO) [40] | Possibility of Habitat improvement | 1 |
Possibility bounds of immigration per gene | [0,1] | |
Size of step for mathematical combination of possibilities | 1 | |
Max emigration (E)and Max immigration (I) | 1 | |
Possibility of mutation | 0.005 | |
Butterfly Optimization Algorithm (BOA) [41] | Quantity of candidates | 5 |
Percent of nomad butterflies | 0.3 | |
Roaming percent | 0.4 | |
Possibility of mutation | 0.1 | |
Rate of sex | 0.85 | |
Possibility of Mating | 0.4 | |
Rate of immigration | 0.5 | |
Equilibrium Optimizer (EO) [42] | \(\:\beta\:\) | 0.04 |
Ac | 0.3 | |
Artificial Ecosystem-based Optimization (AEO) [43] | \(\:\alpha\:\) | 0.2 |
\(\:\beta\:\) | 0.5 | |
\(\:\gamma\:\) | 1 |
