Reduction stage

1. Set the information system of antibacterial plants A=(U,A)

2. Define the indiscernibility matrix M(A)=(cij)

3. Build the discernibility function FA for the information system A as in Equation (1).

4. Reduce M attributes using laws of Rough sets (Upper, and Lower Laws).

5. Define d as number of non-empty rows of reduced M.

6. Build families sets of R0, R1, R2,………… Rd in the as follows:

7. Begin:

8. R0 is empty

9. For i = 1 to d

10. Ri=Si ∪ Ti, where Si={R∈Ri−1:R ∩ Ci ≠∅}, and $Ti={\left(R\cup \left\{a\right\}\right)}_{a\in C_i,R\in R_i,R\cap C_i=\varnothing }$

11. Calculate the accuracy α for each Ri

12. End

13. If αi < 0.6

14. Remove dispensable attribute form each element of Rd

15. REDA (A)= Rd

Optimization Stage

16. Set the Population P as a matrix P = [Ni*Mj] where N is the bacteria type and M is the plant

17. Set the particle is Pij which is the bacteria i on plant j

18. For each particle

19. Initialize position and velocity

20. End For

21. Do

22. For each particle

23. Find in the particle neighborhood, the particles with the best fitness as Pbest and Gbest.

24. Calculate Pi velocity according to the velocity equation

25. Vij(k+1)=wvij+c1r1[pbest-xij(k)]+c2r2[gbest-xij(k)]

26. Update Pi position according to the position equation

27. Xij(k+1)=xij(k)+vij(k+1)

28. If the new position for Pi is less than its current position then

29. Modify the velocity and position for Pi and Pbest and Gbest

30. Else

31. Modify the velocity of Pi and keep its old position

32. End For

33. While maximum iterations or minimum error criteria is not attained