Computer Science and Information Engineering, World Congress on (2009)
Los Angeles, California USA
Mar. 31, 2009 to Apr. 2, 2009
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CSIE.2009.674
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.
Quantum-behaved PSO, Neighborhood Topology Model, Parallel Computing
Jun Sun, Wenbo Xu, Xiaogen Wang, "A Parallel QPSO Algorithm Using Neighborhood Topology Model", Computer Science and Information Engineering, World Congress on, vol. 04, no. , pp. 831-835, 2009, doi:10.1109/CSIE.2009.674