Table 1 Proposed PSOSSO algorithm flowchart.

Salp Swarm Optimization Algorithm (SSO)

1. Initialize the duty cycle (dc) near the ub

2. Calculate the fitness of each search agent (salp)

3. Find the best value and best position

4. F = the best search agent (best position)

5. i = searching agent

6. Update C1 by Eq. (13) for each salp (xi)

Particle Swarm Optimization Algorithm (PSO)

7. Initialize the PSO parameters,

8. Inertia Weight W,

9. Personal Learning Coefficient c1

10. Global Learning Coefficient c2

Hybrid Algorithm (PSOSSO)

11. Update the PSO velocity by Eq. (10)

12. Update PSO position by Eq. (11)

13. If (i == 1)

14. Update leading salp position Eq. (12)

15. Else

16. Update salp follower position Eq. (15)

17. End

18. Amend the salps based on the upper and lower bounds of variables

19. Velocity = salp position divide by the PSO velocity

20. End

21. Update the position dc(i) = dc(i) + velocity