Title :
Impact of tuning parameters on dynamic swarms in PSO-based multiobjective optimization
Author :
Leong, Wen-Fung ; Yen, Gary G.
Author_Institution :
Sch. of Electr. & Comput. Eng., Oklahoma State Univ., Stillwater, OK
Abstract :
In this paper, the improvement of two design components (swarm growing strategy and objective space compression and expansion strategy) from the existing multiple swarms MOPSO, namely DSMOPSO, is presented. In addition, sensitivity analysis is conducted to study the impact of the five tuning parameters on its performance through two performance metrics. Simulation results show the improved design is robust with respect to the tuning parameters.
Keywords :
particle swarm optimisation; PSO-based multiobjective optimization; dynamic swarms; expansion strategy; objective space compression; particle swarm optimization; swarm growing strategy; tuning parameters; Evolutionary computation;
Conference_Titel :
Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1822-0
Electronic_ISBN :
978-1-4244-1823-7
DOI :
10.1109/CEC.2008.4630966
