Title :
Modified particle swarm optimization for unconstrained optimization
Author_Institution :
Dept. of Comput. Sci. & Technol., Dezhou Univ., Dezhou, China
Abstract :
This paper presents a modified particle swarm optimization (PSO) algorithm to improve the performance of standard PSO. The proposed approach is called HPSO, which modifies the original velocity updating equation of PSO. In order to verify the performance of HPSO, we test it on ten well-known benchmark optimization functions. The simulation results show that HPSO obtains better performance than standard PSO on majority of test functions.
Keywords :
particle swarm optimisation; benchmark optimization functions; modified particle swarm optimization; test functions; unconstrained optimization; velocity updating equation; Benchmark testing; Birds; Computational intelligence; Computational modeling; Computer science; Equations; Learning systems; Particle swarm optimization; Space exploration; evolutionary optimization; particle swarm optimization (PSO); unconstrained optimization;
Conference_Titel :
Computer and Automation Engineering (ICCAE), 2010 The 2nd International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-5585-0
Electronic_ISBN :
978-1-4244-5586-7
DOI :
10.1109/ICCAE.2010.5451219