Skip to Main content Skip to Navigation
Conference papers

Two Improvement Strategies for PSO

Abstract : This paper proposed an improved particle swarm optimization algorithm (IPSO) to solve continuous function optimization problems. Two improvement strategies named "Vector correction strategy" and "Jump out of local optimum strategy" were employed in our improved algorithm. The algorithm was tested using 25 newly proposed benchmark instances in Congress on Evolutionary Computation 2005 (CEC2005). The experimental results show that the search efficiency and the ability of jumping out from the local optimum of the IPSO have been significantly improved, and the improvement strategies are effective.
Document type :
Conference papers
Complete list of metadata

Cited literature [8 references]  Display  Hide  Download

https://hal.inria.fr/hal-01055064
Contributor : Hal Ifip <>
Submitted on : Monday, August 11, 2014 - 12:48:50 PM
Last modification on : Thursday, March 5, 2020 - 5:43:10 PM
Long-term archiving on: : Wednesday, November 26, 2014 - 10:00:23 PM

File

Two_Improvement_Strategies_for...
Files produced by the author(s)

Licence


Distributed under a Creative Commons Attribution 4.0 International License

Identifiers

Citation

Quansheng Dou, Shasha Liu, Ping Jiang, Xiuhua Zhou, Zhongzhi Shi. Two Improvement Strategies for PSO. 6th IFIP TC 12 International Conference on Intelligent Information Processing (IIP), Oct 2010, Manchester, United Kingdom. pp.122-129, ⟨10.1007/978-3-642-16327-2_17⟩. ⟨hal-01055064⟩

Share

Metrics