Algorithm 2: Pseudo-code of EODE-PFA

1. Load EODE-PFA parameter 2. Initialize the population 3. Calculate the fitness of initial population 4. Find the number of pathfinders(leaders): LN 5. While K < maximum number of iterations 6.     Calculate elite center using Equation (5) and the bound of leaders 7.     Update parameters: u1, u2, r3, A, ε 8.     for i = 1 to LN 9.            Generate elite opposition-based position using Equation (8) 10.          Generate basic update position using Equation (1) 11.          Check the bound of elite opposition-based position 12.          if elite opposition-based position or basic update position is better than old 13.          Update pathfinder 14.          end 15.   end 16.   for i = LN + 1 to maximum number of populations 17.          Generate 3 random individuals 18.          Generate mutation vector using Equation (11) 19.          Generate trial vector using Equation (12) 20.          Generate basic update position using Equation (2) 21.          if trial vector or basic update position is better than old 22.          Update follower 23.          end 24.   end 25.   Generate new fitness of each members 26. end