Research Article
Simulation Study of Swarm Intelligence Based on Life Evolution Behavior
(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 |
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