Algorithm 2. IPOA for ELD

1: Input: Population size, Dimension, variable bounds Maximum failure count 2: Initialization: Initialize population X and Calculate fitness value using Equation (5) 3: for i = 1: Max_iterations 4:       for j = 1: N 5:         Randomly select an individual 6:         if fit(p) < fit(j) 7:       Update positions by Equation (7) 8:         else 9:       Update positions by Equation (13) 10:        end if 11:        Update positions by Equation (14) 12:        Use algorithm1 update the global optimum solution 13:        Handling boundary conditions 14:        Calculating individual fitness values using Equation (5) 15:        Update the global optimum solution 16:   end for 17: end for 18: Calculate fuel cost using Equation (1) 19: Output: Optimal cost, Unit’s output