Title :
An Enhanced Particle Swarm Optimization Algorithm with Passive Congregation
Author_Institution :
Dept. of Inf. Eng., Hunan Urban Constr. Coll., Xiangtan, China
Abstract :
This paper presents a particle swarm optimization (PSO) with passive congregation to improve the performance of standard PSO (SPSO). Passive congregation is an important biological force preserving swarm integrity. By introducing passive congregation to PSO, information can be transferred among individuals of the swarm. A particle swarm optimizer with passive congregation (PSOPC) is tested with a set of 8 benchmark functions with 30 dimensions and compared to a global version of SPSO (GSPSO), a local version of SPSO (LSPSO), and PSO with a constriction factor (CPSO), respectively. Experimental results indicate that the PSO with passive congregation improves the search performance on the benchmark functions significantly.
Keywords :
Benchmark testing; Biological system modeling; Birds; Educational institutions; Equations; Evolutionary computation; Machine vision; Man machine systems; Marine animals; Particle swarm optimization; optimization; particle swarm optimization; passive congregation;
Conference_Titel :
Machine Vision and Human-Machine Interface (MVHI), 2010 International Conference on
Conference_Location :
Kaifeng, China
Print_ISBN :
978-1-4244-6595-8
Electronic_ISBN :
978-1-4244-6596-5
DOI :
10.1109/MVHI.2010.193