As of August 2024, International Journal "Notes on Intuitionistic Fuzzy Sets" is being indexed in Scopus.
Please check our Instructions to Authors and send your manuscripts to nifs.journal@gmail.com. Next issue: September/October 2024.

Open Call for Papers: International Workshop on Intuitionistic Fuzzy Sets • 13 December 2024 • Banska Bystrica, Slovakia/ online (hybrid mode).
Deadline for submissions: 16 November 2024.

Issue:Intuitionistic fuzzy sets in group decision making

From Ifigenia, the wiki for intuitionistic fuzzy sets and generalized nets
Revision as of 17:56, 28 August 2024 by Vassia Atanassova (talk | contribs) (Text replacement - ""Notes on IFS", Volume" to ""Notes on Intuitionistic Fuzzy Sets", Volume")
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to navigation Jump to search
shortcut
http://ifigenia.org/wiki/issue:nifs/2/1/15-32
Title of paper: Intuitionistic fuzzy sets in group decision making
Author(s):
Eulalia Szmidt
Systems Research Institute, Polish Academy of Sciences
Janusz Kacprzyk
Systems Research Institute, Polish Academy of Sciences
kacprzyk@ibspan.waw.pl
Published in: "Notes on Intuitionistic Fuzzy Sets", Volume 2 (1996) Number 1, pages 15—32
Download:  PDF (3430  Kb, File info)
Abstract: The determination of solutions in group decision making via intuitionistic fuzzy sets is considered. The point of departure is a collection of individual intuitionistic fuzzy preference relations. We also assume a (traditional) fuzzy majority equated with a fuzzy linguistic quantifier. A solution is derived either directly from the individual intuitionistic fuzzy preference relations or by constructing first a social intuitionistic fuzzy preference relation. Two solution concepts are proposed, the intuitionistic fuzzy core and consensus winner.
Keywords: Group decision making, fuzzy preference relations, intuitionistic fuzzy preference relations, core, consensus winner.
AMS Classification: 0ЗЕ72
References:
  1. Atanassow K.T. (1986). Intuitionistic Fuzzy Sets. Fuzzy Sets and Systems, 20, 87-96.
  2. Atanassov K.T. (1988). Review and new results on intuitionistic fuzzy sets. IM-MFAIS-1.
  3. Atanassov K.T. (1989). More on intuitionistic fuzzy sets. Fuzzy Sets and Systems, 33, 3-45.
  4. Barrett, C.R. and Pattanaik, P.K. (1990). Aggregation of fuzzy preferences. In J. Kacprzyk and M. Fedrizzi, (Eds.): Multiperson Decision Making Models using Fuzzy Sets and Possibility Theory, Kluwer, Dordrecht, pp. 155—162.
  5. Blin, J.M. and Whinston, A.P. (1973). Fuzzy sets and social choice. J. of Cybernetics 4, 17-22.
  6. Bustince H., Burillo P. (1996). Structures on intuitionistic fuzzy relations, Fuzzy Sets and Systems, 3, 293-303.
  7. Dubois D., Prade H. (1980). Fuzzy sets and Systems. New York.
  8. Fedrizzi, M., Kacprzyk, J. and Nurmi, H. (1993). Consensus degrees under fuzzy majorities and fuzzy preferences using OWA (ordered weighted average) operators, Control and Cybernetics, 22, 71—80.
  9. Kacprzyk, J. (1984). Collective decision making with a fuzzy majority rule, Proc. WOGSC Congress, AFCET, Paris, pp. 153-159.
  10. Kacprzyk, J. (1985a). Some 'commonsense solution concepts in group decision making via fuzzy linguistic quantifiers. In J. Kacprzyk and R.R. Yager (Eds.): Management Decision Support Systems Using Fuzzy Sets and Possibility Theory, Verlag TV*{U}V Rheinland, Cologne, pp. 125-135.
  11. Kacprzyk, J. (1985b). Group decision-making with a fuzzy majority via linguistic quantifiers. Part I: A consensory-like pooling; Part II: A competitive-like pooling, Cybernetics and Systems: an Int. J., 16, 119—129 (Part I), 131-144 (Part II).
  12. Kacprzyk, J. (1986). Group decision making with a fuzzy linguistic majority, Fuzzy Sets and Systems, 18, 105—118.
  13. Kacprzyk, J. (1987). On some fuzzy cores and 'soft' consensus measures in group decision making. In J.C. Bezdek (Ed.): The Analysis of Fuzzy Information, Vol. 2, CRC Press, Boca Raton, pp. 119-130.
  14. Kacprzyk, J. and Fedrizzi,M., Eds. (1990). Multiperson Decision Making Models Using Fuzzy Sets and Possibility Theory, Kluwer, Dordrecht.
  15. Kacprzyk, J. and Fedrizzi, M. (1995). A fuzzy majority in group DM and consensus via the OWA operators with importance qualification, Proc. of dFT'95 — Current Issues in Fuzzy Technologies (Trento, Italy), pp. 128—137.
  16. Kacprzyk, J., Fedrizzi, M. and Nurmi, H. (1990). Group decision making with fuzzy majorities represented by linguistic quantifiers. In J.L. Verdegay and M. Delgado (Eds.): Approximate Reasoning Tools for Artificial Intelligence, Verlag TV*{U}V Rheinland, Cologne, pp. 126-145.
  17. Kacprzyk, J., Fedrizzi, M. and Nurmi, H. (1992). Group decision making and consensus under fuzzy preferences and fuzzy majority, Fuzzy Sets and Systems, 49,21-31.
  18. Kacprzyk, J. and Nurmi, H. (1989). Linguistic quantifiers and fuzzy majorities for more realistic and human-consistent group decision making. In G. Evans, W. Karwowski and M. Wilhelm (Eds.): Fuzzy Methodologies for Industrial and Systems Engineering, Elsevier, Amsterdam, pp. 267-281.
  19. Kacprzyk, J., Nurmi, H. and Fedrizzi, M., Eds. (1996). Consensus under Fuzziness, Kluwer, Boston.
  20. Kacprzyk, J. and Roubens, M., Eds. (1988). Non-Conventional Preference Relations in Decision Making, Springer—Verlag, Heidelberg.
  21. Nurmi, H. (1981). Approaches to collective decision making with fuzzy preference relations, Fuzzy Sets and Systems, 6, 249—259.
  22. Nurmi, H., Fedrizzi, M. and Kacprzyk, J. (1990). Vague notions in the theory of voting. In J. Kacprzyk and M. Fedrizzi (Eds.): Multiperson Decision Making Models Using Fuzzy Sets and Possibility Theory, Kluwer, Dordrecht, pp. 43-52.
  23. Nurmi, H. and Kacprzyk, J. (1991). On fuzzy tournaments and their solution concepts in group decision making, Europ. J. of Operational Research, 51, 223-232.
  24. Tanino, T. (1984). Fuzzy preference orderings in group decision making, Fuzzy Sets and Systems, 12, 117-131.
  25. Tanino, T. (1990). On group decision making under fuzzy preferences. In J. Kacprzyk and M. Fedrizzi (Eds.): Multiperson Decision Making Models using Fuzzy Sets and Possibility Theory, Kluwer, Dordrecht, pp. 172—185.
  26. Zadeh, L.A. (1983). A computational approach to fuzzy quantifiers in natural languages. Computers and Maths with Appls, 9, 149—184.
Citations:

The list of publications, citing this article may be empty or incomplete. If you can provide relevant data, please, write on the talk page.