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Sensitivity and Uncertainty Analysis in Optimization Programs Using an Evolutionary Approach

  • Conference paper
Advances in Artificial Intelligence (IBERAMIA 2000, SBIA 2000)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1952))

  • 922 Accesses

Abstract

Many practical problems require the calculation of an optimum (global) according to a general program P. However the model on which the optimal is based may be incomplete in the sense that important uncertainties have not been considered. In order to evaluate the effects of the uncertainty of the parameters, the decision-maker needs to evaluate the range of variation of program P. In this work a two-step evolutionary approach to analyze uncertainties in optimization programs is presented. The proposed approach combines the two proven techniques of Cellular Evolutionary Strategies (CES) and Evolutionary Strategies (ES).

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© 2000 Springer-Verlag Berlin Heidelberg

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Rocco, C.M., Miller, A., Moreno, J.A., Carrasquero, N., Medina, M. (2000). Sensitivity and Uncertainty Analysis in Optimization Programs Using an Evolutionary Approach. In: Monard, M.C., Sichman, J.S. (eds) Advances in Artificial Intelligence. IBERAMIA SBIA 2000 2000. Lecture Notes in Computer Science(), vol 1952. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44399-1_50

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  • DOI: https://doi.org/10.1007/3-540-44399-1_50

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41276-2

  • Online ISBN: 978-3-540-44399-5

  • eBook Packages: Springer Book Archive

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