Title :
Dynamic multi-swarm particle swarm optimizer with local search
Author :
Liang, J.J. ; Suganthan, P.N.
Author_Institution :
Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ.
Abstract :
In this paper, the performance of a modified dynamic multi-swarm particle swarm optimizer (DMS-PSO) on the set of benchmark functions provided by CEC2005 is reported. Different from the existing multi-swarm PSOs and local versions of PSO, the swarms are dynamic and the swarms´ size is small. The whole population is divided into many small swarms, these swarms are regrouped frequently by using various regrouping schedules and information is exchanged among the swarms. The quasi-Newton method is combined to improve its local search ability
Keywords :
Newton method; particle swarm optimisation; search problems; dynamic multiswarm particle swarm optimizer; local search problem; quasiNewton method; Acceleration; Birds; Convergence; Diversity reception; Equations; Evolutionary computation; Optimization methods; Particle swarm optimization; Testing; Topology;
Conference_Titel :
Evolutionary Computation, 2005. The 2005 IEEE Congress on
Conference_Location :
Edinburgh, Scotland
Print_ISBN :
0-7803-9363-5
DOI :
10.1109/CEC.2005.1554727
