Algorithm A1. Identifying acceleration factors using an artificial bee colony algorithm.

1: Read the $n$ experimental data values of $\left(t_{ij},P_{ij}\right)$. Then, store them in the matrix; 2: Initialize related parameters of ABC algorithm: $ite{r}_{\max }$ (maximum number of iterations), $Limit$ (maximum number of iterations before abandoning the solution), $d$ (parameter number), $N$ (initial solution number); 3: Initialize the solution vector using Equation (12); 4: Evaluate the fitness value of the initial solution using Equation (14); 5: Set cycle to 1; 6: Repeat; 7: For each employed bee:   {   Produce new solution $v_i$ by Equation (13);   Calculate the value $fi{t}_i$ by Equation (14);   Apply greedy selection process.   } 8: Calculate the probability values $P(x_i)$ for the produced solutions by Equation (15); 9: For each onlooker bee:   {   Select a solution I depending on $P\left(x_i\right)$;   Repeat step (7).   } 10: If a candidate solution does not change in more than $Limit$ iterations, then replace it with a new random solution produced by a scout bee using Equation (16);