Algorithm 1. Modified CS algorithm

1. Begin

2. Generate initial population of n nests (solutions) $x_i$, i = 1, 2, …, n

3. Define objective function f(x); x = (x1, x2, …, xd);

4. Set the range of $\alpha$ and $Pa$: ${\alpha }_{\text{min}}$, ${\alpha }_{\text{max}}$, $P{a}_{\text{min}}$, $P{a}_{\text{max}}$

5. Set the range of the nest(solution): $X_{\text{min}}$, $X_{\text{max}}$

6. Set the maximum number of iterations: N_itertotal

7. For all $x_i$ do

8. Calculate the fitness $F_i=f(x_i)$

9. End For

10. N_iter = 1

11. While (N_iter < N_itertotal) do

12. For all $x_i$ do

13. Compute the step size for $L{e}^{\prime }vy$ flight using Equation (6)

14. Generate a new cuckoo ($x_j$) from the nest $x_i$ randomly by taking Lévy flight

15. If ($x_j>X_{\text{max}}$) then

16. $x_j\leftarrow X_{\text{max}}$

17. End If

18. If ($x_j<X_{\text{min}}$) then

19. $x_j\leftarrow X_{\text{min}}$

20. End If

21. Calculate the fitness $F_j=f(x_j)$

22. Choose a random nest ($x_k$) among n nest randomly

23. If ($F_j>F_k$) then

24. $x_j\leftarrow x_k$

25. $F_j\leftarrow F_k$

26. End If

27. End For

28. Keep the current global optimal fitness: $f_{\text{min}}$

29. Compute the probability $Pa$ using Equation (7)

30. A fraction ($Pa$) of worse nests abandoned and new ones/solutions are built/generated correspondingly

31. For all the nests (say, $x_i$) to be built/generated do

32. If ($x_i>X_{\text{max}}$) then

33. $x_i\leftarrow X_{\text{max}}$

34. End If

35. If ($x_i<X_{\text{min}}$) then

36. $x_i\leftarrow X_{\text{min}}$

37. End If

38. Calculate the fitness $F_i=f(x_i)$ and evaluate its quality/fitness $F_i$

39. Keep best solutions (or nests with quality solutions)

40. End For

41. Rank all the solutions and find the current best

42. End While

43. End