Title :
Dynamic Multi-Swarm Particle Swarm Optimization for Multi-objective optimization problems
Author :
Liang, J.J. ; Qu, B.Y. ; Suganthan, P. ; Niu, Ben
Author_Institution :
Sch. of Electr. Eng., Zhengzhou Univ., Zhengzhou, China
Abstract :
In this paper, Dynamic Multi-Swarm Particle Swarm Optimizer (DMS-PSO) which was first designed for solving single objective optimizations problems is extended to solve Multi-objective optimization problems with constraints. Through analysis, novel pbest and lbest updating criteria which are more suitable for solving Multi-objective optimization problems are proposed. By combining the external archive and the novel updating criteria, excellent performance is achieved by DMS-MO-PSO on eight benchmark test functions.
Keywords :
particle swarm optimisation; dynamic multiswarm particle swarm optimization; lbest updating criteria; multiobjective optimization problems; pbest updating criteria; single objective optimization problems; Convergence; Educational institutions; Measurement; Optimization; Particle swarm optimization; Radio frequency; Sorting; Particle swarm optimizer; dynamic multi-swarm optimizer; multi-objective optimization;
Conference_Titel :
Evolutionary Computation (CEC), 2012 IEEE Congress on
Conference_Location :
Brisbane, QLD
Print_ISBN :
978-1-4673-1510-4
Electronic_ISBN :
978-1-4673-1508-1
DOI :
10.1109/CEC.2012.6256416
