An analysis of bare bones particle swarm

Feng Pan*, Xiaohui Hu, Russ Eberhart, Yaobin Chen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

34 Citations (Scopus)

Abstract

The Bare Bones Particle Swarm (BBPS) is evolved from the canonical Particle Swarm Optimizer (PSO). The velocity term of the canonical PSO is removed in BBPS and replaced by Gaussian sampling strategy. There is no parameter tuning and it is much easier to implement. In the paper, it is proven that the BBPS can be mathematically deduced from the canonical PSO and a more general formula of BBPS is also presented. The results presented in the paper represent initial results of an ongoing research project effort.

Original languageEnglish
Title of host publication2008 IEEE Swarm Intelligence Symposium, SIS 2008
DOIs
Publication statusPublished - 2008
Event2008 IEEE Swarm Intelligence Symposium, SIS 2008 - St. Louis, MO, United States
Duration: 21 Sept 200823 Sept 2008

Publication series

Name2008 IEEE Swarm Intelligence Symposium, SIS 2008

Conference

Conference2008 IEEE Swarm Intelligence Symposium, SIS 2008
Country/TerritoryUnited States
CitySt. Louis, MO
Period21/09/0823/09/08

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