| Input: |
| Master swarm size (), slave swarm size (), the dimensionality of the problem space |
| (), maximum number of fitness evolution (iterMax), objective function () |
| (1) Randomly initialize the position and velocity of all particles in the master swarm. |
| (2) Randomly initialize the position and velocity of all particles in the slave swarm. |
| (3) Calculate the fitness values of and , |
| (4) Set and to be and for each |
| particle of the master swarm and slave swarm, respectively. |
| (5) Set the particle with the best fitness of the master swarm to be , and set the particle |
| with the best fitness of the slave swarm to be . |
| (6) Set generation , the counter . |
| (7) while ≤ iterMax do |
| (8) for do |
| (9) for do |
| (10) Update the dimensional velocity according to (11), and Update the dimensional |
| position according to (2). |
| (11) end for |
| (12) Calculate the fitness value ; |
| (13) if then |
| (14) ; ; |
| (15) if then |
| (16) ; ; |
| (17) end if |
| (18) end if |
| (19) end for |
| (20) for do |
| (21) for do |
| (22) Update the dimensional velocity according to (14), and Update the dimensional |
| position according to (2); |
| (23) end for |
| (24) Calculate the fitness value ; |
| (25) if then |
| (26) ; ; |
| (27) if then |
| (28) ; ; ; |
| (29) else |
| (30) ; |
| (31) end if |
| (32) end if |
| (33) end for |
| (34) if then |
| (35) ; |
| (36) end if |
| (37) ; |
| (38) end while |
| (39) Set the global best position |
| (40) return Gb |
