Abstract
The concept of the consensus reaching process supporting is presented in the context of group decision making. Methods proposed to support this process concern four issues: individual preferences representation, measuring the degree of agreement in the group, means to moderate the discussion in the group and determining the group choice. Solutions proposed here attempt to mirror the way a human being perceives related concepts and methods. It is attained through modelling of the individual preferences with fuzzy preference relations and through the employment of so-called fuzzy majority for the degree of consensus measuring, group’s structure analysis and preferences aggregation.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Literature
Kacprzyk J, Fedrizzi M. A’ soft’ measure of consensus in the setting of partial (fuzzy) preferences. European Journal of Operational Research 1988; 34: 316–325.
Zadeh LA. A computational approach to fuzzy quantifiers in natural languages. Comp. and Maths, with Appls. 1983; 9: 149–184.
Zadeh LA. A computational theory of dispositions. International Journal of Intelligent Systems 1987; 2: 39–64.
Nurmi H. Approaches to collective decision making with fuzzy preference relations. Fuzzy Sets and Systems 1981; 6:249–259.
Fishbum PC. Nontransitive preferences in decision theory. Paper prepared for the Fifth International Conference on the Foundations and Applications of Utility, Risk and Decision Theory, Duke University, June 10-13, 1990.
Lehrer K, Wagner C. Rational Consensus in Science and Society. Dordrecht, Boston, London: D. Reidel Publishing Company, 1981.
Cholewa W. Aggregation of fuzzy opinions — an axiomatic approach. Fuzzy Sets and Systems 1985; 17: 249–258.
Watabe K, Holsapple CW, Whinston AB. Coordinator support in a nemawashi decision process. Decision Support Systems 1992; 8: No. 2.
Fedrizzi M, Kacprzyk J, Zadrozny S. An interactive multi-user decision support system for consensus reaching processes using fuzzy logic with linguistic quantifiers. Decision Support Systems 1988; 4: 313–327.
Zadrozny S. Computer based consensus reaching support employing the elements of fuzzy logic. Ph.D. Thesis, IBS PAN, Warszawa 1993 (in Polish).
Sen A. K. Collective Choice and Social Welfare. Edinburgh: Oliver & Boyd, 1970.
Switalski Z. “Choice functions associated with fuzzy preference relations.” In Non — conventional Preference Relations in Decision Making, J. Kacprzyk, M. Roubens, eds. Berlin: Springer-Verlag, 1988.
Barrett CR, Pattanaik PK, Salles M. On choosing rationally when preferences are fuzzy. Fuzzy Sets and Systems 1990; 34: 197–212
Kacprzyk J. Group decision making with a fuzzy majority via linguistic quantifiers. Part I: A consensory — like pooling. Cybernetics and Systems: an Int. Journal 1985; 16: 119–129.
Kacprzyk J: Group decision making with a fuzzy majority via linguistic quantifiers. Part II: A competitive — like pooling. Cybernetics and Systems: an Int Journal 1985; 16:131–144.
Kacprzyk J: “Fuzzy logic with linguistic quantifiers: a tool for better modeling of human evidence aggregation processes?” In Fuzzy Sets in Psychology, T. Zetenyi, ed. Amsterdam: North — Holland, 1
Owsinski JW. A new method of cluster analysis with the global objective fonction. Ph.D. Thesis, IBS PAN, Warszawa 1991 (in Polish).
Owsinski JW. On a new naturally indexed quick clustering method with a global objective function. Applied Stochastic Models and Data Analysis 1990; 6:157–171.
Montero de Juan F. J. Aggregation of fuzzy opinion in a non-homogeneous group. Fuzzy Sets and Systems 1987; 25: 15–20.
Dubois D., Koning J.-L. Social choice axioms for fuzzy set aggregation. Fuzzy Sets and Systems 1991; 43: 257–274.
Fung L. W. and Fu K. S. “An axiomatic approach to rational decision making in a fuzzy environment”. In Fuzzy Sets and Their Applications to Cognitive and Decision Processes, L. A. Zadeh, K. S. Fu, T. Tanaka, M. Shimura, eds. New York: Academic Press, 1975.
Dubois D., Prade H. A review of fuzzy set aggregation connectives. Information Sciences 1985; 36: 85–121.
Trillas E., Valverde L. “On mode and implication in approximate reasoning”. In Approximate Reasoning in Expert Systems, M. M. Gupta, A. Kandel, W. Bandler, J. B. Kiszka. eds. Amsterdam: North-Holland, 1985.
Fedrizzi M., Kacprzyk J., Owsinski J. W., Zadrozny S. Consensus reaching via a GDSS with fuzzy majority and clustering of preference profiles. Annals of Operations Research 1994; 51: 127–139.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1997 Springer Science+Business Media New York
About this chapter
Cite this chapter
Zadrożny, S. (1997). An Approach to the Consensus Reaching Support in Fuzzy Environment. In: Kacprzyk, J., Nurmi, H., Fedrizzi, M. (eds) Consensus Under Fuzziness. International Series in Intelligent Technologies, vol 10. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-6333-4_5
Download citation
DOI: https://doi.org/10.1007/978-1-4615-6333-4_5
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4613-7908-9
Online ISBN: 978-1-4615-6333-4
eBook Packages: Springer Book Archive