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DC Element | Wert | Sprache |
---|---|---|
dc.contributor.author | Sudholt, Dirk | de |
dc.contributor.author | Witt, Carsten | de |
dc.date.accessioned | 2009-05-12T16:01:46Z | - |
dc.date.available | 2009-05-12T16:01:46Z | - |
dc.date.issued | 2008-02 | de |
dc.identifier.uri | http://hdl.handle.net/2003/26148 | - |
dc.identifier.uri | http://dx.doi.org/10.17877/DE290R-9031 | - |
dc.description.abstract | We investigate the runtime of the Binary Particle Swarm Optimization (PSO) algorithm introduced by Kennedy and Eberhart (1997). The Binary PSO maintains a global best solution and a swarm of particles. Each particle consists of a current position, an own best position and a velocity vector used in a probabilistic process to update the particle s position. We present lower bounds for a broad class of implementations with swarms of polynomial size. To prove upper bounds, we transfer a fitness-level argument well-established for evolutionary algorithms (EAs) to PSO. This method is then applied to estimate the expected runtime on the class of unimodal functions. A simple variant of the Binary PSO is considered in more detail. The 1-PSO only maintains one particle, hence own best and global best solutions coincide. Despite its simplicity, the 1-PSO is surprisingly efficient. A detailed analysis for the function OneMax shows that the 1-PSO is competitive to EAs. | en |
dc.language.iso | en | de |
dc.relation.ispartofseries | Reihe CI; 241-08 | de |
dc.subject.ddc | 004 | de |
dc.title | Runtime analysis of binary PSO | en |
dc.type | Text | de |
dc.type.publicationtype | report | de |
dcterms.accessRights | open access | - |
Enthalten in den Sammlungen: | Sonderforschungsbereich (SFB) 531 |
Dateien zu dieser Ressource:
Datei | Beschreibung | Größe | Format | |
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24108.pdf | DNB | 235.53 kB | Adobe PDF | Öffnen/Anzeigen |
Diese Ressource ist urheberrechtlich geschützt. |
Diese Ressource ist urheberrechtlich geschützt.
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