his.sePublications
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
Metamodel-assisted Global Search Using a Probing Technique
University of Skövde, School of Technology and Society.ORCID iD: 0000-0003-3973-3394
University of Skövde, School of Technology and Society.
University of Skövde, School of Technology and Society.ORCID iD: 0000-0003-0111-1776
2007 (English)In: The IAENG International Conference on Artificial Intelligence and Applications (ICAIA'07), International Association of Engineers, 2007, 83-88 p.Conference paper, (Refereed)
Abstract [en]

This paper presents a new metamodel-assisted metaheuristic algorithm for optimisation problems involving computationally expensive simulations. The algorithm, called Global Probing Search, is a population-based algorithm designed for global optimisation. The main idea of the algorithm is to introduce a probing phase in the creating of the new generation of the population. In this probing phase, a large number of candidate solutions are generated and a computationally cheap metamodel function is used for choosing the most promising candidates to transfer to the next generation. This approach could significantly enhance the efficiency of the optimisation process by avoiding wasting valuable evaluation time on solutions that are likely to be inferior. During the optimisation, the accuracy of the metamodel is constantly improved through on-line updating. The proposed algorithm is implemented on a real-world optimisation problem and initial results indicate that the algorithm show good performance in comparison with a standard Genetic Algorithm and an existing metamodel-assisted metaheuristic.

Place, publisher, year, edition, pages
International Association of Engineers, 2007. 83-88 p.
Keyword [en]
Terms—Metaheuristic, Optimisation, Simulation, Metamodel, Neural Network.
Identifiers
URN: urn:nbn:se:his:diva-2037ISI: 000246800600015Scopus ID: 2-s2.0-84888342486ISBN: 978-988-98671-4-0 OAI: oai:DiVA.org:his-2037DiVA: diva2:32313
Conference
International MultiConference of Engineers and Computer Scientists 2007, IMECS 2007, Kowloon, Hong Kong, 21 March 2007 through 23 March 2007
Available from: 2008-05-09 Created: 2008-05-09 Last updated: 2015-12-18Bibliographically approved

Open Access in DiVA

No full text

Scopus

Search in DiVA

By author/editor
Persson, AnnaGrimm, HenrikNg, Amos
By organisation
School of Technology and Society

Search outside of DiVA

GoogleGoogle Scholar

Total: 937 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