Simulation Study of Swarm Intelligence Based on Life Evolution Behavior

Algorithm 2

(1) Begin

(2)  Initialize positions and associated velocity of all particles

(3)  Evaluate the fitness values of all particles

(4)  Set the current position as

(5)  Set = 0.25()

(6) Build initial external archives based on -dominance

(7)  Calculate crowding distance of each particle

(8)  While (fitcout < Max_FES) && (k < iteration)

(9)   For each particle ()

(10)    Update particle velocity and position by (1) and (15)

(11)     Update

(12)    Evaluate the fitness values of current particle

(13)    End for

(14)    If internal environment change

(15)     Run _Mutation and _Crossing

(16)    End if

(17)    If external environment change

(18)     Run _Mutation and _Crossing

(19)    End if

(20)   Updating the relative parameters

(21)   Increase the generation count

(22)  Update the external archive

(23)    End While

(24)     Output the results

(25) End Begin