Model updating using genetic algorithms with sequential niche technique

Faisal Shabbir, Piotr Omenzetter

Research output: Contribution to journalArticle

17 Citations (Scopus)
5 Downloads (Pure)

Abstract

Structural model updating is an optimization problem where parameters that minimize the errors between the model and the actual structure are sought. However, multiple solutions may be present. Global optimization algorithms are efficient optimisation tools but are not fully immune to missing the global minimum. To increase the chance of finding the global minimum, a combination of genetic algorithm with sequential niche technique is proposed. The method performs systematic search to find multiple minima and facilitates detecting the minimum that best describes the system. The technique is applied to experimental data from a simple laboratory structure and a full-scale pedestrian cable-stayed bridge, and also tested on a deceptive problem using the numerical model of a space frame.
Original languageEnglish
Pages (from-to)166-182
Number of pages17
JournalEngineering Structures
Volume120
Early online date3 May 2016
DOIs
Publication statusPublished - 1 Aug 2016

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Genetic algorithms
Footbridges
Cable stayed bridges
Global optimization
Numerical models

Keywords

  • cable-stayed bridge
  • deceptive problem
  • global optimization algorithms
  • inverse problem
  • model updating
  • multiple minima
  • genetic algorithm
  • sequential niche technique
  • structural optimization

Cite this

Model updating using genetic algorithms with sequential niche technique. / Shabbir, Faisal; Omenzetter, Piotr.

In: Engineering Structures, Vol. 120, 01.08.2016, p. 166-182.

Research output: Contribution to journalArticle

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