New Methods of Decision Making Under Uncertainty
International Journal of Economic Behavior and Organization
Volume 3, Issue 2-1, April 2015, Pages: 5-9
Received: Dec. 4, 2014; Accepted: Dec. 9, 2014; Published: Dec. 27, 2014
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Authors
Sándor Molnár, Institute of Mathematics and Informatics, Szent István University, Páter K. u.1., H-2100, Gödöllő, Hungary
Ferenc Szidarovszky, Department of Applied Mathematics, University of Pécs, Ifjúság u. 6, H-7624, Pécs, Hungary
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Abstract
The classical formula of certainty equivalent is reconsidered. Based on a modified proof of the original formula several alternative methods are derived with different orders of magnitude of their errors. This new method is then compared with the classical formula in a computer study showing the advantage of the new approach. Practical applications are also outlined to illustrate the methodology.
Keywords
Uncertainity, Certainty Equivalent, Economic Application
To cite this article
Sándor Molnár, Ferenc Szidarovszky, New Methods of Decision Making Under Uncertainty, International Journal of Economic Behavior and Organization. Special Issue: Recent Developments of Economic Theory and Its Applications. Vol. 3, No. 2-1, 2015, pp. 5-9. doi: 10.11648/j.ijebo.s.2015030201.12
References
[1]
Bellman, R. and L.A.Zadeh (1970) Decision Making in a Fuzzy Environment. Management Science, 17(4), 141-164.
[2]
Csábrági A, Molnár M (2011) Role of Non-Conventional Energy Sources in Supplying Future Energy Needs, Bulletin of the Szent István University, Gödöllő (Special Issue: p. 216). (2011)
[3]
DeGroot, M.H. (1970) Optimal Stochastic Decisions. New York: McGraw-Hill.
[4]
Hatvani I G, Magyar N, Zessner M, Kovács J, Blaschke A P (2014) The Water Framework Directive: Can more information be extracted from groundwater data? A case study of Seewinkel, Burgenland, eastern Austria, Hydrogeology Journal 22:(4) pp. 779-794. (2014)
[5]
Kall, P. and S.W. Wallace (1994) Stochastic Programming. Chichester: Wiley.
[6]
Kovács J, Kovács S, Magyar N, Tanos P, Hatvani I G, Anda A (2014) Classification into homogeneous groups using combined cluster and discriminant analysis, Environmental Modelling & Software 57: pp. 52-59. (2014)
[7]
Molnár Márk (2014) Opportunities for Hungary under the Stability Reserve of the EU ETS, Journal of Central European Green Innovation 2:(2) pp. 105-114. (2014)
[8]
Molnar, S., F. Szidarovszky. Game Theory, Multiobjective Optimization, Conflict Resolution, Differential Games (in Hungarian). Computerbooks, Budapest, Hungary, 2011.
[9]
Prekopa, A. (1995) Stochastic Programming. Dordrecht: Kluwer Academic Publishers.
[10]
Sargent, T.J. (1979) Macroeconomic Theory. New York: Academic Press.
[11]
Szidarovszky, F., M. Gershon and L. Duckstein (1986) Techniques for Multi-objective Decision Making in Systems Management. Amsterdam: Elsevier.
[12]
Szidarovszky, F. and S. Yakowitz (1978) Principles and Procedures of Numerical Analysis. New York: Plenum Press.
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