Global Optimization Solution of Robust Estimation

Robust estimation has proved to be a valuable approach to adjust a surveying network when there are systematic or gross errors in the observations or systematic errors in the functional model. In this paper, the authors propose to solve robust estimation as a global optimization problem. In particular, the simulated annealing method and genetic algorithms are applied. The usual strategy of iteratively reweighed least squares is analyzed vs. the global optimization approach. Results show that in problematic cases robust estimation is not truly robust unless performed by a global optimization method.

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  • Supplemental Notes:
    • Abstract reprinted with permission from ASCE
  • Authors:
    • Baselga, Sergio
  • Publication Date: 2007-8


  • English

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  • Accession Number: 01055274
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Aug 17 2007 12:52PM