EconPapers    
Economics at your fingertips  
 

Biases in Particle Swarm Optimization

William M. Spears, Derek T. Green and Diana F. Spears
Additional contact information
William M. Spears: Swarmotics LLC, USA
Derek T. Green: University of Arizona, USA
Diana F. Spears: Swarmotics LLC, USA

International Journal of Swarm Intelligence Research (IJSIR), 2010, vol. 1, issue 2, 34-57

Abstract: The most common versions of particle swarm optimization (PSO) algorithms are rotationally variant. It has also been pointed out that PSO algorithms can concentrate particles along paths parallel to the coordinate axes. In this paper, the authors explicitly connect these two observations by showing that the rotational variance is related to the concentration along lines parallel to the coordinate axes. Based on this explicit connection, the authors create fitness functions that are easy or hard for PSO to solve, depending on the rotation of the function.

Date: 2010
References: Add references at CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 4018/jsir.2010040103 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jsir00:v:1:y:2010:i:2:p:34-57

Access Statistics for this article

International Journal of Swarm Intelligence Research (IJSIR) is currently edited by Yuhui Shi

More articles in International Journal of Swarm Intelligence Research (IJSIR) from IGI Global
Bibliographic data for series maintained by Journal Editor ().

 
Page updated 2025-03-19
Handle: RePEc:igg:jsir00:v:1:y:2010:i:2:p:34-57