Skip to main content

A General Form of Fuzzy Group Decision Making Choice Functions under Fuzzy Preference Relations and Fuzzy Majority

  • Chapter
Fuzzy Applications in Industrial Engineering

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 201))

  • 1723 Accesses

Abstract

A general form of a collective choice rule in group decision making under fuzzy preferences and a fuzzy majority is proposed. It encompasses some well-known choice rules. Our point of departure is the fuzzy majority based linguistic aggregation rule (solution concept) proposed by Kacprzyk [11–13]. This rule is viewed here from a more general perspective, and the fuzzy majority – meant as a fuzzy linguistic quantifier – is dealt with by using Yager’s [42] OWA operators. The particular collective choice rules derived via the general scheme proposed are shown to be applicable in the case of nonfuzzy preferences too. Moreover, a relation to Zadeh’s concept of a protoform is mentioned in this context.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Aizerman M., Aleskerov F. (1995) Theory of Choice. North-Holland, Amsterdam.

    MATH  Google Scholar 

  2. Barrett C.R, Pattanaik PK, Salles M. (1990) On choosing rationally when preferences are fuzzy. Fuzzy Sets and Systems 34: 197–212.

    Article  MATH  MathSciNet  Google Scholar 

  3. Billot A. (1991) Aggregation of preferences: the fuzzy case, Theory and Decision 30: 51–93.

    Article  MATH  MathSciNet  Google Scholar 

  4. Fedrizzi M., Kacprzyk J., Nurmi H. (1993) Consensus degrees under fuzzy majorities and fuzzy preferences using OWA (ordered weighted average) operators. Control and Cybernetics 22: 71–80.

    MathSciNet  Google Scholar 

  5. Fedrizzi M., Kacprzyk J. Nurmi H. (1996) How different are social choice functions: a rough sets approach, Quality and Quantity 30: 87–99.

    Google Scholar 

  6. Fedrizzi M., Kacprzyk J., Zadrożny S. (1988) An interactive multi-user decision support system for consensus reaching processes using fuzzy logic with linguistic quantifiers, Decision Support Systems 4: 313–327.

    Article  Google Scholar 

  7. Fodor J.C., Roubens M. (1994) Fuzzy Preference Modelling and Multicriteria Decision Support. Kluwer, Dordrecht.

    MATH  Google Scholar 

  8. Herrera F., Herrera-Viedma E. (1997) Aggregation operators for linguistic weighted information, IEEE Transactions on Systems, Man and Cybernetics SMC-27: 646–656.

    Google Scholar 

  9. Herrera F., Herrera-Viedma E. (2000) Choice functions and mechanisms for linguistic preference relations, European Journal of Operational Research 120: 144–161.

    Article  MATH  MathSciNet  Google Scholar 

  10. Herrera F., Herrera-Viedma E., Verdegay J.L. (1996) Direct approach processes in group decision making using linguistic OWA operators, Fuzzy Sets and Systems 79: 175–190.

    Article  MATH  MathSciNet  Google Scholar 

  11. Kacprzyk J. (1985) Group decision making with a fuzzy majority via linguistic quantifiers. Part I: A consensory - like pooling. Cybernetics and Systems: an Int. Journal 16: 119–129.

    MATH  MathSciNet  Google Scholar 

  12. Kacprzyk J. (1985) Group decision making with a fuzzy majority via linguistic quantifiers. Part II: A competitive - like pooling. Cybernetics and Systems: an Int. Journal 16: 131–144.

    MATH  MathSciNet  Google Scholar 

  13. Kacprzyk J. (1986) Group decision making with a fuzzy majority, Fuzzy Sets and Systems 18: 105–118.

    Article  MATH  MathSciNet  Google Scholar 

  14. Kacprzyk J., Fedrizzi M. (1986) ‘Soft’ consensus measures for monitoring real consensus reaching processes under fuzzy preferences, Control and Cybernetics 15: 309–323.

    MathSciNet  Google Scholar 

  15. Kacprzyk J., Fedrizzi M. (1988) A ‘soft’ measure of consensus in the setting of partial (fuzzy) preferences, European Journal of Operational Research 34: 316–325.

    Article  MathSciNet  Google Scholar 

  16. Kacprzyk J., Fedrizzi M. (1989) A ‘human-consistent’ degree of consensus based on fuzzy logic with linguistic quantifiers, Mathematical Social Sciences 18: 275–290.

    Article  MATH  MathSciNet  Google Scholar 

  17. Kacprzyk J., Fedrizzi M. (eds.) (1990) Multiperson Decision Making Problems Using Fuzzy Sets and Possibility Theory, Kluwer, Dordrecht/Boston/London.

    Google Scholar 

  18. Kacprzyk J., Fedrizzi M., Nurmi H. (1992) Group decision making and consensus under fuzzy preferences and fuzzy majority, Fuzzy Sets and Systems 49: 21–31.

    Article  MATH  MathSciNet  Google Scholar 

  19. Kacprzyk J., Nurmi H. (1988) Group decision making under fuzziness, in R. Słowiński (ed.): Fuzzy Sets in Decision Analysis, Operations Research and Statistics, Kluwer, Boston, pp. 103–136.

    Google Scholar 

  20. Kacprzyk J., Nurmi H., Fedrizzi M. (eds.) (1996) Consensus under Fuzziness, Kluwer, Boston.

    Google Scholar 

  21. Kacprzyk J., Nurmi H., Fedrizzi M. (1999) Group Decision Making and a Measure of Consensus under Fuzzy Preferences and a Fuzzy Linguistic Majority, in: LA. Zadeh and J. Kacprzyk (eds.): Computing with Words in Information/Intelligent Systems. Part 2. Foundations. Physica-Verlag, Heidelberg and New York, pp. 233–243.

    Google Scholar 

  22. Kacprzyk J., Roubens M. (eds.) (1988) Non-conventional Preference Relations in Decision Making, Springer - Verlag, Berlin and New York.

    MATH  Google Scholar 

  23. Kacprzyk J., Zadrożny S. (2000) Collective choice rules under linguistic preferences: an example of the computing with words/perceptions paradigm, Proceedings of 9th IEEE International Conference on Fuzzy Systems (FUZZIEEE’ 2000), San Antonio, USA, pp. 786–791.

    Google Scholar 

  24. Kacprzyk J., Zadrożny S. (2001) Computing with words in decision making through individual and collective linguistic choice rules, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 9: 89–102.

    Article  MATH  MathSciNet  Google Scholar 

  25. Kacprzyk J., Zadrożny S. (2002) Collective choice rules in group decision making under fuzzy preferences and fuzzy majority: a unified OWA operator based approach, Control and Cybernetics 31(4): 937–948.

    Google Scholar 

  26. Kacprzyk J., Zadrożny S., Fedrizzi M. (1997) An interactive GDSS for consensus reaching using fuzzy logic with linguistic quantifiers, in D. Dubois, H. Prade and R.R. Yager (eds.): Fuzzy Information Engineering - A Guided Tour of Applications, Wiley, New York, pp. 567–574.

    Google Scholar 

  27. Kitainik L. (1993). Fuzzy Decision Procedures with Binary Relations: Towards a Unified Theory. Kluwer Academic Publishers, Boston/Dordrecht/London.

    MATH  Google Scholar 

  28. Nurmi H. (1981) Approaches to collective decision making with fuzzy preference relations. Fuzzy Sets and Systems 6: 249–259.

    Article  MATH  MathSciNet  Google Scholar 

  29. Nurmi H. (1983) Voting procedures: a summary analysis. British Journal of Political Science 13: 181–208.

    Article  Google Scholar 

  30. Nurmi H. (1987) Comparing Voting Systems. Reidel, Dordrecht.

    Google Scholar 

  31. Nurmi H. (1988) Assumptions on individual preferences in the theory of voting procedures. In J. Kacprzyk and M. Roubens (eds.): Non-Conventional Preference Relations in Decision Making, Springer-Verlag, Heidelberg, pp. 142–155.

    Google Scholar 

  32. Nurmi H., Fedrizzi M., 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.

    Google Scholar 

  33. Nurmi H., Kacprzyk J. (2000) Social choice under fuzziness: a perspective, in J. Fodor, B. De Baets and P. Perny (eds.): Preferences and Decisions under Incomplete Knowledge. Physica-Verlag (Springer-Verlag), Heidelberg and New York, pp. 107–130.

    Google Scholar 

  34. Nurmi H., Kacprzyk J. (1991) On fuzzy tournaments and their solution concepts in group decision making. European Journal of Operational Research 51: 223–232.

    Article  MATH  Google Scholar 

  35. Nurmi H., Kacprzyk J., Fedrizzi M. (1996) Probabilistic, fuzzy and rough concepts in social choice, European Journal of Operational Research 95: 264–277.

    Article  MATH  Google Scholar 

  36. Ovchinnikov S. (1990) Modelling valued preference relations, In J. Kacprzyk and M. Fedrizzi (eds.) : Multiperson Decision Making Models Using Fuzzy Sets and Possibility Theory, Kluwer, Dordrecht, pp. 64–70.

    Google Scholar 

  37. Roubens M. (1989) Some properties of choice functions based on valued binary relations, European Journal of Operational Research 40: 309–321.

    Article  MATH  MathSciNet  Google Scholar 

  38. Schwartz T. (1986) The Logic of Collective Choice. Columbia University Press, New York.

    Google Scholar 

  39. Sen A. K. (1970) Collective Choice and Social Welfare. Oliver and Boyd, Edinburgh.

    MATH  Google Scholar 

  40. Świtalski Z. (1988) Choice functions associated with fuzzy preference relations, in J. Kacprzyk, M. Roubens (eds.): Non - conventional Preference Relations in Decision Making, Springer-Verlag, Berlin, pp. 106–118.

    Google Scholar 

  41. Van de Walle B., De Baets B., Kerre E. E. (1998). A plea for the use of łukasiewicz triplets in fuzzy preference structures. Part 1: General argumentation. Fuzzy Sets and Systems 97: 349–359.

    Article  MathSciNet  Google Scholar 

  42. Yager R. R. (1988) On ordered weighted averaging aggregation operators in multi-criteria decision making. IEEE Transactions on Systems, Man and Cybernetics SMC-18: 183–190.

    Article  MathSciNet  Google Scholar 

  43. Yager R. R. (1994) Interpreting linguistically quantified propositions. International Journal of Intelligent Systems 9: 541–569.

    MATH  Google Scholar 

  44. Yager R. R., Kacprzyk, J. (eds.) (1997) The Ordered Weighted Averaging Operators: Theory and Applications, Kluwer, Boston.

    Google Scholar 

  45. Zadeh L A. (1983) A computational approach to fuzzy quantifiers in natural languages. Comp. and Maths. with Appls. 9: 149–184.

    Article  MATH  MathSciNet  Google Scholar 

  46. Zadeh L. A. (1987) A computational theory of dispositions. International Journal of Intelligent Systems 2: 39–64.

    MATH  Google Scholar 

  47. Zadeh L. A. (2002) A prototype-centered approach to adding deduction capabilities to search engines – the concept of a protoform. BISC Seminar, 2002, University of California, Berkeley.

    Google Scholar 

  48. Zadrożny S (1996) An approach to the consensus reaching support in fuzzy environment, in J. Kacprzyk, H. Nurmi and M. Fedrizzi (eds.): Consensus under Fuzziness. Kluwer, Boston, pp. 83–109.

    Google Scholar 

  49. Zadrożny S., Kacprzyk J. (1999) Collective choice rules: a classification using the OWA operators. Proceedings of EUSFLAT-ESTYLF Joint Conference, Palma de Mallorca, Spain, pp. 21–24.

    Google Scholar 

  50. Zadrożny S., Kacprzyk J. (2000) An approach to individual and collective choice under linguistic preferences, Proceedings of 8th International Conference on Information Processing and Management of Uncertainty in Knowledge- based Systems IPMU 2000, Madrid, pp. 462–469.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer

About this chapter

Cite this chapter

Kacprzyk, J., Zadrożny, S. (2006). A General Form of Fuzzy Group Decision Making Choice Functions under Fuzzy Preference Relations and Fuzzy Majority. In: Kahraman, C. (eds) Fuzzy Applications in Industrial Engineering. Studies in Fuzziness and Soft Computing, vol 201. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-33517-X_12

Download citation

  • DOI: https://doi.org/10.1007/3-540-33517-X_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-33516-0

  • Online ISBN: 978-3-540-33517-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics