| Algorithm. IPSO () |
| Input: |
| Output: , |
| Begin |
| (1) Initialize the parameters including population size , the dimension size , |
| the maximum iteration number , and the current iterative count |
| (2) Generate the initial population and initial velocity. The initial population and initial velocity for each |
| particle are randomly generated as follows: |
| Population = |
| Velocity = |
| where and are the position and velocity at the th iteration for the th particle, |
| respectively. is the dimension of each particle. , are the minimum and maximum value of |
| each point belonging to the th dimension, respectively. , are the minimum and maximum |
| value of each point belonging to the th dimension, respectively. |
| (3) Calculate the fitness value of each particle and record it as: , record the th particle's |
| best fitness and its corresponding position as: , , St. , |
| (4) Calculate the population’s best fitness and its corresponding position , St. |
| (5) Compute population centroid by (9) with the weighted coefficient computed by (15), |
| compute best individual centroid by (6). |
| (6) For to do |
| (6.1) Compute by (10), and generate a random number ; |
| (6.2) If |
| (6.2.1) Update by (19) |
| (6.2.2) For to do |
| Update and by (12) and (3) respectively, compute |
| If then , , , |
| End If |
| End |
| Else |
| (6.2.3) Update by (19) |
| (6.2.4) For to do |
| Update and by (7) and (3) respectively, compute |
| If then , , , |
| End If |
| End |
| End If |
| (6.3) Compute and set , where |
| (6.4) Compute population centroid by (9) with the weighted coefficient computed by (15), |
| compute best individual centroid by (6). |
| (6.5) let |
| End |
| (7) output , |
| End |
