Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Adaptive Particle Swarm Optimization (APSO) for multimodal function optimization
KTH, School of Information and Communication Technology (ICT).
2009 (English)In: International Journal of Engineering and Technology, ISSN 0975-4024, Vol. 1, no 3, 98-103 p.Article in journal (Refereed) Published
Abstract [en]

This research paper presents a new evolutionary optimization model based on the particle swarm optimization (PSO) algorithm that incorporates the flocking behavior of a spider. The search space is divided into several segments like the net of a spider. The social information sharing among the swarms are made strong and adaptive. The main focus is on the fitness of the swarms adjusting to the learning factors of the PSO. The traditional Particle Swarm Optimization algorithms converges rapidly during the initial stage of a search, but in course of time becomes steady considerably and can get trapped in a local optima. On the other hand in the proposed model the swarms are provided with the intelligence of a spider which enables them to avoid premature convergence and also help them to escape from local optima. The proposed approaches have been validated using a series of benchmark test functions with high dimensions. Comparative analysis with the traditional PSO algorithm suggests that the new algorithm significantly improves the performance when dealing with multimodal functions.

Place, publisher, year, edition, pages
2009. Vol. 1, no 3, 98-103 p.
Keyword [en]
Evolutionary algorithm, Multimodal function, Particle swarm optimization (PSO)
National Category
Other Engineering and Technologies
Identifiers
URN: urn:nbn:se:kth:diva-152382Scopus ID: 2-s2.0-78650371524OAI: oai:DiVA.org:kth-152382DiVA: diva2:754474
Note

QC 20141010

Available from: 2014-10-10 Created: 2014-09-26 Last updated: 2017-12-05Bibliographically approved

Open Access in DiVA

No full text

Scopus

Search in DiVA

By author/editor
Hossen, Md Sakhawat
By organisation
School of Information and Communication Technology (ICT)
In the same journal
International Journal of Engineering and Technology
Other Engineering and Technologies

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 47 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf