Title :
A Parallel QPSO Algorithm Using Neighborhood Topology Model
Author :
Wang, Xiaogen ; Sun, Jun ; Xu, Wenbo
Author_Institution :
Sch. of Educ., Jiangnan Univ., Wuxi, China
fDate :
March 31 2009-April 2 2009
Abstract :
Quantum-behaved Particle Swarm Optimization algorithm (QPSO) is a new variant of Particle Swarm Optimization (PSO). It is also a population-based search strategy, which has good performance on well-known numerical test problems. QPSO is based on the standard PSO and inspired by the theory of quantum physics. In this paper, we explore the parallelism of QPSO and implement the parallel QPSO based on the Neighborhood Topology Model, which is much closer to the nature world. The performance of the parallel QPSO is compared to PSO and QPSO on a set of benchmark functions. The results show that the parallel QPSO outperforms the other two algorithms.
Keywords :
parallel algorithms; particle swarm optimisation; search problems; topology; neighborhood topology model; parallel QPSO algorithm; population-based search strategy; quantum physics theory; quantum-behaved particle swarm optimization; Computer science; Computer science education; Equations; High performance computing; Information technology; Parallel processing; Particle swarm optimization; Quantum mechanics; Sun; Topology; Neighborhood Topology Model; Parallel Computing; Quantum-behaved PSO;
Conference_Titel :
Computer Science and Information Engineering, 2009 WRI World Congress on
Conference_Location :
Los Angeles, CA
Print_ISBN :
978-0-7695-3507-4
DOI :
10.1109/CSIE.2009.674