DocumentCode
2068191
Title
Modified particle swarm optimization and its application in multimodal function optimization
Author
Na Li ; Song Zhu
Author_Institution
State Key Lab. of Software Eng., Wuhan Univ., Wuhan, China
fYear
2011
fDate
16-18 Dec. 2011
Firstpage
375
Lastpage
378
Abstract
In multimodal optimization, the basic particle swarm optimization is easy to duplicate and miss points of the optimal value. To solve this problem, a modified particle swarm optimization algorithm, called BNPSO, is proposed. This modified particle swarm optimization algorithm is based on the niche particle swarm optimization (NPSO) algorithm, and implemented a Bernoulli trial. It is proved theoretically that the algorithm BNPSO is much more effective than the algorithm NPSO for multimodal function optimization problems. However, the time complexity of the new scheme is increased. Testing of the algorithm indicate that the algorithm BNPSO has better perform in stability and convergence.
Keywords
particle swarm optimisation; Bernoulli trial; NPSO; modified particle swarm optimization; multimodal function optimization application; niche particle swarm optimization; optimal value; Algorithm design and analysis; Genetic algorithms; Mathematical model; Optimization; Particle swarm optimization; Signal processing algorithms; Vectors; Bernoulli trial; multimodal function optimization; niche technology; particle swarm optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Transportation, Mechanical, and Electrical Engineering (TMEE), 2011 International Conference on
Conference_Location
Changchun
Print_ISBN
978-1-4577-1700-0
Type
conf
DOI
10.1109/TMEE.2011.6199221
Filename
6199221
Link To Document