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).
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Saltelli A., M. Scott (1997), editors: “The role of sensitivity analysis in the corroboration of models and its links to model structural and parametric uncertainty”, special issue, Reliability Engineering and System Safety, 57(1).
Shooman M.(1990): “Probabilistic reliability: An engineering Approach”, Second Edition, R. Krieger Pub. Co., Malabar, Florida
Constantinides A. (1994): “Basic Reliability”, 1994 Annual Reliability and Maintainability Symposium, Anaheim, California, USA.
Granger M., M. Henrion (1990): Uncertainty, Cambridge University Press, 1990
Kauffman A., M. Gupta (1991): “Introduction to Fuzzy Arithmetic”, Van Nostrand Reynolds
Moore R. (1979): “Methods and Applications of interval analysis”. SIAM. Philadelphia
Alefeld G., J. Herzberger (1983): “Introduction to Interval Computations”, Academic Press, New York
Hansen E. (1992): “Global Optimisation Using Interval Analysis”, Marcel Dekker, Inc., New York
SIGLA/X Group (1998): “Modal Interval Analysis: An Introduction”, http://ima.udg.es/SIGLA/
Rocco C., A.J. Miller (1999): “Selection of the Appropriate Technique for Sensitivity/Uncertainty Analysis: A decision tree approach”, Probabilistic Safety Assessment, Washington
Dekker R. (1996): “Application of maintenance optimisation models: a review and analysis”, Reliability Engineering and System Safety, 51, 229–240.
Ushakov I.(1994): Handbook of Reliability Engineering, John Wiley & Son, New York
Kursawe F. (1993): “Evolution Strategies-Simple “Models of Natural Process?””, Revue Internationale de Systemique, Vol 7, No. 5, 1993
Kursawe F. (1992): “Towards Self-Adapting Evolution Strategies”, Proc. Of the Tenth International Conference on Multiple Criteria Decision Making, G Tzeng and P. Yu (Eds), Taipei
Navarro J., J.A. Moreno and N. Carrasquero (1999): Evolutionary Multi-Objective Optimization of Simulation Models, Proceedings of the Second International Symposium on Artificial Intelligence, Cuba, 1999
Schwefel H.P, Th. Bäck. (1995): “Evolution Strategies I: Variants and their computational implementation”, in J. Periaux and G. Winter (Eds), Genetic Algorithm in Engineering and Computer Science, John Wiley & Sons
Bäck Th., H.P. Schwefel (1996): “Evolutionary Computation: An overview”, Proc. Of the 1996 IEEE Int’l Conf. On Evolutionary Computation (IECC’96), Nagoya, Japan, 20–29, IEEE Press, NY
Medina M., J.A. Moreno and N. Carrasquero (1998): “Estrategias Evolutivas Celulares para la Optimización de Funciones”, Progresso em Inteligência Artificial (IBERAMIA’98), Actas do 6° Congresso Iberoamericano de Inteligência Artificial, Lisboa, Portugal, 227–238, EdiÇôes Colibri, 1600 Lisboa
Wildeman R., R. Dekker (1997): “Dynamic influences in multi-component maintenance”, Quality and Reliability Engineering International, vol 13, 199–207
Goyal S.K., M.I. Kusy (1989): “Determining Economic Maintenance Frequency for a Family of Machine”, Journal of the Operational Research Society, No. 38
Goyal S.K., A. Gunesakaran (1992): “Determining Economic Maintenance Frequency of a Transport Fleet”, International Journal of Systems Science, No 4
Rocco C. M.(1997): “Variability Analysis of Electronic Systems: Classical and Interval Methods”. Proceeding of the Annual Reliability and Maintainability Symposium, Philadelphia, USA
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2000 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
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
Download citation
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