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Author
Sniedovich Moshe (University of Melbourne, Australia)
Title
The Art and Science of Modeling Decision-Making Under Severe Uncertainty
Source
Decision Making in Manufacturing and Services, 2007, vol. 1, nr 1/2, s. 111-136, rys., tab., bibliogr. 19 poz.
Keyword
Podejmowanie decyzji w warunkach niepewności, Luka informacyjna, Modelowanie matematyczne
Decision making under uncertainty, Information gap, Mathematical modeling
Note
summ.
Abstract
For obvious reasons, models for decision-making under severe uncertainty are austere. Simply put, there is precious little to work with under these conditions. This fact highlights the great importance of utilizing in such cases the ingredients of the mathematical model to the fullest extent, which in turn brings under the spotlight the art of mathematical modeling. In this discussion we examine some of the subtle considerations that are called for in the mathematical modeling of decision-making under severe uncertainty in general, and worst-case analysis in particular. As a case study we discuss the lessons learnt on this front from the Info-Gap experience.(original abstract)
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Bibliography
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  1. M. Avriel, Nonlinear programming analysis and methods, Prentice-Hall, 1976.
  2. Y. Ben-Haim, Information Gap Decision Theory, Academic Press, 2001.
  3. Y. Ben-Haim, Info-Gap Decision Theory, Elsevier, 2006.
  4. Y. Ben-Haim, Value-at-risk with info-gap uncertainty, The Journal of Risk Finance, 6 (5) (2005), 388-403.
  5. A. Ben-Tal, L. El Ghaoui, A. Nemirovski, Mathematical Programming, Special issue on Robust Optimization, Volume 107 (1-2), 2006.
  6. S.D. French, Decision Theory, Ellis Horwood, 1988.
  7. R. Grunig, ¨ R. Kuhn, ¨ Successful decision-making, Springer-Verlag. 2005.
  8. S.F. Hillier, G.J. Lieberman, Introduction to Operations Research, 8th edition, McGraw Hill, 2005.
  9. R.E. Markland, J.R. Sweigart, Quantitative Methods: Applications to Managerial decision-making, John Wiley, 1987.
  10. P. Kouvelis, G. Yu, Robust Discrete Optimization and Its Applications, Kluwer, 1997.
  11. C.T. Ragsdale, Spreadsheet Modeling and Decision Analysis, Thomson, 2004.
  12. B. Rustem, M. Howe, Algorithms for Worst-case Design and Applications to Risk Management, Princeton University Press, 2002.
  13. M. Sniedovich, OR/MS Games: 3. The Counterfeit coin problem, INFORMS Transactions in Education, 3 (2003), 2, 32-41.
  14. M. Sniedovich, What is wrong with Info-Gap? An Operations Research Perspective, Working Paper MS-1-06, presented at the ASOR Mini-Conference, Dec 1, 2006, Melbourne, Australia, 2006.
  15. R. Steuer, Multiple Criteria Optimization: Theory, Computation and Application, John Wiley, 1985.
  16. H. Vladimirou, S.A. Zenios, Stochastic Programming and Robust Optimization, Chapter 12 in Gal T. and Greenberg H.J. (Eds) Advances in Sensitivity Analysis and Parametric Programming, Kluwer, 1997.
  17. A. Wald, Statistical decision functions which minimize the maximum risk, The Annals of Mathematics, 46 (1945), 2, 265-280.
  18. A. Wald, Statistical Decision Functions, John Wiley, 1950.
  19. W.L. Winston, Operations Research: Applications and Algorithms, Duxbury Press, 1994.
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ISSN
2300-7087
Language
eng
URI / DOI
http://dx.doi.org/10.7494/dmms.2007.1.2.111
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