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Exploiting parallelization and synergy in derivative free optimization
Linköping University, Department of Mathematics, Optimization . Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Mathematics, Optimization . Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0001-5907-0087
2020 (English)Report (Other academic)
Abstract [en]

Real life optimization often concerns difficult objective functions, in two aspects, namely that gradients are unavailable, and that evaluation of the objective function takes a long time. Such problems are often attacked with model building algorithms, where an approximation of the function is constructed and solved, in order to find a new promising point to evaluate. We study several ways of saving time by using parallel calculations in the context of model building algorithms, which is not trivial, since such algorithms are inherently sequential. We present a number of ideas that has been implemented and tested on a large number of known test functions, and a few new ones. The computational results reveal that some ideas are quite promising.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2020. , p. 18
Series
LiTH-MAT-R, ISSN 0348-2960 ; 2020:4
Keywords [en]
Derivative-free optimization, parallel algorithms, applications of mathematical programming
National Category
Mathematics
Identifiers
URN: urn:nbn:se:liu:diva-164133ISRN: LiTH-MAT-R--2020/04--SEOAI: oai:DiVA.org:liu-164133DiVA, id: diva2:1412566
Available from: 2020-03-06 Created: 2020-03-06 Last updated: 2020-03-12Bibliographically approved

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Olsson, Per-MagnusHolmberg, Kaj

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • 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