Algorithm 1. The pseudocode of conventional GWO

1. Generate a population Xi (i = 1, 2, …, n) randomly 2. Initialize the parameters of GWO (max_iteration, a, A and C) 3. Calculate the fitness values and assign α, β and δ 4. While (t < max_iteration) 5.         For each grey wolf 6.                 Update the position of the current grey wolf using Equations (6)–(8) 7.         End for 8.         Update a, A and C 9.         Amend the grey wolves’ positions beyond boundary limits 10.       Calculate the fitness values of the new positions 11.       Update the α, β and δ 12.        t = t + 1 13. End while 14. Return the position of α