Premium
Active target particle swarm optimization
Author(s) -
Zhang YingNan,
Hu QingNi,
Teng HongFei
Publication year - 2008
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.1207
Subject(s) - particle swarm optimization , position (finance) , swarm behaviour , computation , computer science , mathematical optimization , mathematics , algorithm , economics , finance
We propose an active target particle swarm optimization (APSO). APSO uses a new three‐target velocity updating formula, i.e. the best previous position, the global best position and a new target position (called active target). In this study, we distinguish APSO from EPSO (extended PSO)/PSOPC (PSO with passive congregation) by the different methods of getting the active target. Note that here EPSO and PSOPC are the two existing methods for using three‐target velocity updating formula, and getting the third (active) target from the obtained positions by the swarm. The proposed APSO gets the active (third) target using complex method, where the active target does not belong to the existing positions. We find that the APSO has the advantages of jumping out of the local optimum and keeping diversity; however, it also has the disadvantages of adding some extra computation expenses. The experimental results show the competitive performance of APSO when compared with PSO, EPSO, and PSOPC. Copyright © 2007 John Wiley & Sons, Ltd.