Global Optimization Solution of Robust Estimation
Publication: Journal of Surveying Engineering
Volume 133, Issue 3
Abstract
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 the present paper we propose to solve robust estimation as a global optimization problem. In particular, we will apply the simulated annealing method and genetic algorithms. The usual strategy of iteratively reweighed least squares is analyzed versus 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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Acknowledgments
The writer is grateful to biologist María Salinas for her assistance with GA techniques as well as to the anonymous reviewers for their valuable suggestions, corrections, and constructive comments.
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Published In
Journal of Surveying Engineering
Volume 133 • Issue 3 • August 2007
Pages: 123 - 128
Copyright
© 2007 ASCE.
History
Received: Aug 18, 2006
Accepted: Jan 17, 2007
Published online: Aug 1, 2007
Published in print: Aug 2007
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