Model updating using genetic algorithms with sequential niche technique

Faisal Shabbir, Piotr Omenzetter

Research output: Contribution to journalArticlepeer-review

47 Citations (Scopus)
11 Downloads (Pure)


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
Early online date3 May 2016
Publication statusPublished - 1 Aug 2016


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


Dive into the research topics of 'Model updating using genetic algorithms with sequential niche technique'. Together they form a unique fingerprint.

Cite this