Abstract
In this paper a recent axiomatic approach to fuzzy preference modelling is summarized. These results are applied to multiple criteria decision making problems in order to find aggregation rules which give the same global strict preference independently of their use before or after individual considerations.
Partially supported by OTKA
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
C. Alsina, On a family of connectives for fuzzy sets, Fuzzy Sets and Systems 16 (1985) 231–235.
M. Baas and H. Kwakernaak, Rating and ranking of multiple aspect alternatives using fuzzy sets, Automatica 13 (1977) 47–58.
D. Dubois and H. Prade, Weighted minimum and maximum in fuzzy set theory, Inform. Sci. 39 (1986) 205–210.
D. Dubois and H. Prade, On the ranking of ill-known values in possibility theory, Fuzzy Sets and Systems 43 (1991) 311–317.
J. C. Fodor, Strict preference relations based on weak t-norms, Fuzzy Sets and Systems 43 (1991) 327–336.
J. C. Fodor, An axiomatic approach to fuzzy preference modelling, Fuzzy Sets and Systems (to appear in 52 (1992)).
J. C. Fodor and M. Roubens, Fuzzy preference modelling — an overview, Annales Univ. Sci. Budapest., Sectio Computatorica XII (1991) 93–100.
J. C. Fodor and M. Roubens, Aggregation and scoring procedures in multicriteria decision making problems, IEEE International Conference on Fuzzy Systems (San Diego, USA, 1992) 1261–1267.
J. C. Fodor and M. Roubens, Aggregation of strict preference relations in MCDM procedures, in: V. Novák and al. (Eds), Fuzzy Approach to Reasoning and Decision-Making, Kluwer Acad., Dordrecht, 1991.
J. C. Fodor and M. Roubens, Valued preference structures, submitted.
J. C. Fodor and M. Roubens, Aggregation, Ranking and Choice Procedures with Applications to Multiple Criteria Decision Making Methods dealing with valued binary relations (book in preparation).
S. Ovchinnikov, On aggregation of max-product transitive valued binary relations, IEEE International Conference on Fuzzy Systems (San Diego, USA, 1992) 1245–1252.
S. Ovchinnikov and M. Roubens, On strict preference relations, Fuzzy Sets and Systems 43 (1991) 319–326.
S. Ovchinnikov and M. Roubens, On fuzzy strict preference, indifference and incomparability relations, Fuzzy Sets and Systems 47 (1992) 313–318 and 49 (1992) 15-20.
P. Perny, Modelisation, agrégation et exploitation de préférences floues dans une problématique de rangement, Ph.D. Thesis, Université Paris-Dauphine, 1992.
M. Roubens and Ph. Vincke, Preference Modelling, (Springer-Verlag, Berlin, 1985).
M. Roubens and Ph. Vincke, Fuzzy possibility graphs and their application to ranking fuzzy numbers, in: J. Kacprzyk and M. Roubens, Eds., Non-Conventional Preference Relations in Decision Making, Lecture Notes in Economics and Mathematical Systems Vol. 301 (Springer-Verlag, Berlin, 1988) 119–128.
B. Roy, ELECTRE III: Un algorithme de classement fondé sur un-e représentation plane des préférences en présence de critères multiples, Cahiers du Centre d’Etudes de Recherche Opérationnelle, 20 (1978), 3–24.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1993 Springer Science+Business Media Dordrecht
About this chapter
Cite this chapter
Fodor, J.C., Roubens, M. (1993). Preference Modelling and Aggregation Procedures with Valued Binary Relations. In: Lowen, R., Roubens, M. (eds) Fuzzy Logic. Theory and Decision Library, vol 12. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-2014-2_3
Download citation
DOI: https://doi.org/10.1007/978-94-011-2014-2_3
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-010-4890-3
Online ISBN: 978-94-011-2014-2
eBook Packages: Springer Book Archive