Algorithm 3: The IPSO algorithm
1:	Set various parameters of the IPSO.
2:	Initialize the positions and velocities of population randomly, and calculate the fitness value.
3:	Enter main loop until the end condition is triggered.
4:	Calculate the mutation rate according to Equation (7).
5:	For each voter or follower
6:	If random value <= mutation rate
7:	If random value <= fixed rate
8:	Update the voter or follower with random mutation according to Equation (8).
9:	Else
10:	Update the voter or follower with Cauchy mutation according to Equation (9).
11:	End
12:	Else
13:	Update the voter or follower without mutation according to Equation (5) or Equation (6).
14:	End
15:	Calculate the individual fitness with the custom cost function and up- date the individual pbest.
16:	Update the support rate according to Equation (3).
17:	If the support rate of the voter is over fixed value, then change this voter to follower.
18:	End
19:	Calculate the competition rate according to Equation (2).
20:	For each candidate
21:	If random value <= competition rate
22:	Update the candidate with competition according to Equation (4).
23:	Else
24:	Update the candidate without competition according to Equation (4).
25:	End
26:	Calculate the individual fitness with the custom cost function and up- date the individual pbest.
27:	End
28:	Reselect the leader and candidates.
29:	If any candidate changes, then change its followers to voters.
30:	i = i + 1.
31:	Exit main loop to end the optimization process.