An Innovative Excited-ACS-IDGWO Algorithm for Optimal Biomedical Data Feature Selection

Algorithm 1: Pseudocode for the standard CS.

1 Begin:

2 Initialize

3 Define objective function , where is the number of dimensions

4 Generate initial population of host bird nests,

5 while  or any other stopping criteria

6 Generate a new cuckoo (solution) randomly via Le’vy flight according to Equation (1)

7 Evaluate the fitness of the new cuckoo,

8 Randomly choose a nest from among the host nests (For example )

9 if then

10 Replace nest j by the new cuckoo

11 end

12 Abandon a fraction of worst nests and generate new ones according to Equation (6)

13 Keep best solutions (or those nests with quality solutions)

14 Rank these solutions, then keep the current best

15 end while

16 Report the final best

17 end

Algorithm 1: Pseudocode for the standard CS.