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Multicriteria decision aid methods are used to analyze decision problems including a series of alternative decisions evaluated on several criteria. They most often assume that perfect information is available with respect to the evaluation of the alternative decisions. However, in practice, imprecision, uncertainty or indetermination are often present at least for some criteria. This is a limit of most multicriteria methods. In particular the PROMETHEE methods do not allow directly for taking into account this kind of imperfection of information. We show how a general framework can be adapted to PROMETHEE and can be used in order to integrate different imperfect information models such as a.o. probabilities, fuzzy logic or possibility theory. An important characteristic of the proposed approach is that it makes it possible to use different models for different criteria in the same decision problem.
Rocznik
Tom
Strony
9--8
Opis fizyczny
Bibliogr. 15 poz.
Twórcy
autor
autor
- Telfer School of Management, University of Ottawa, Ottawa, Canada., benamor@telfer.uottawa.ca
Bibliografia
- [1] M. Behzadian, R.B. Kazemzadh, A. Albadvi D. and M. Aghdasi, "PROMETHEE: A comprehensive literature review on methodologies and applications", European Journal of Operational Research, in press.
- [2] S. Ben Amor, K. Jabeur and J-M. Martel, "Multiple criteria aggregation procedure for mixed evaluations", European Journal of Operational Research, 181(3), pp. 1506-1515, 2007.
- [3] J.P. Brans and B. Mareschal "PROMCALC & GAIA: A new decision support system for multicriteria decision aid", Decision Support Systems, 12, pp.297-310, 1994.
- [4] J.P. Brans and B. Mareschal "PROMETHEE Methods" in Multiple Criteria Decision Analysis: State of the Art, edited by J. Figueira, S. Greco and M. Ehrgott, pp.163-196, Kluwer, 2005.
- [5] D. Dubois, H. Prade and S. Sandri, "On possibility/probability transformations", Lowen R, Roubens M (eds), Fuzzy Logic: State of the Art, Kluwer Academic Publ., Dordrecht, pp. 103-112, 1993.
- [6] J. Figueira, S. Greco and M. Ehrgott, Multiple Criteria Decision Analysis: State of the Art., Kluwer, 2005.
- [7] A. Langewish and F. Choobineh, "Stochastic dominance tests for ranking alternatives under ambiguity", European Journal of Operational Research, 95, pp.139-154, 1996.
- [8] B. Mareschal, "Stochastic multicriteria decision-making under uncertainty". European Journal of Operational Research 26 (1), 58-64, 1986.
- [9] B. Mareschal and J.P. Brans "Geometrical representations for MCDA", European Journal of Operational Research, 39, pp. 284-292, 1989.
- [10] J-M. Martel and K. Zaras, "Stochastic dominance in multicriterion analysis under risk", Theory and Decision, 39, 31-49, 1995.
- [11] G. Munda, Multicriteria evaluation in a fuzzy environment, Physica-Verlag, Heidelberg, 1995.
- [12] B. Roy, Méthodologie Multicritère d'Aide à la Décision, Economica, Paris, 1985.
- [13] G. Shafer, A Mathematical Theory of Evidence, Princeton University Press, Princeton N.J., 1976.
- [14] Ph. Smets, "Decision making in the TBM: the necessity of the pignistic transformation", International Journal o Approximate Reasoning, 38, pp. 133-147, 2005.
- [15] Ph. Smets, "Constructing the pignistic probability function in a context of uncertainty", in: Henrion M, Shachter RD, Kanal LN and Lemmer JF (eds), Uncertainty in Artificial Intelligence 5, North Holland, Amsterdam, pp.29-40, 1990.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPP2-0020-0040