Skip to main content
SpringerLink
Log in
Book cover

Granular, Soft and Fuzzy Approaches for Intelligent Systems pp 101–118Cite as

On Practical Applicability of the Generalized Averaging Operator in Fuzzy Decision Making

  • Chapter
  • First Online:

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 344))

Abstract

Many different types of aggregation operators have been suggested as decision functions for multicriteria fuzzy decision making. This paper investigates the practical applicability of generalized averaging operator as decision functions in modeling human decision behavior. Previously published numerical data is used in the analysis and the results are compared with those obtained from compensatory operators. The numerical data suggests that the generalized averaging operator may be used for modeling human decision behavior.

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

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   109.99
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

Learn about institutional subscriptions

References

  1. Beliakov, G., Pradera, A., Calvo, T.: Aggregation Functions: A Guide for Practitioners. Springer, Berlin (2007)

    MATH  Google Scholar 

  2. Bellman, R.E., Zadeh, L.A.: Decision-making in a fuzzy environment. Manag. Sci. 17(4), 141–164 (1970)

    Article  MathSciNet  MATH  Google Scholar 

  3. da Costa Sousa, J.M., Kaymak, U.: Fuzzy Decision Making in Modeling and Control. World Scientific Series in Robotics and Intelligent Systems, vol. 27. World Scientific, New Jersey (2002)

    Book  MATH  Google Scholar 

  4. de Herder, W.A.W.: Multicriteria beslissen met vage criteria. Master’s thesis report, Delft University of Technology, Control Lab. Fac. of El. Eng. Delft (1986). (A86.005–(364))

    Google Scholar 

  5. Dombi, J.: Basic concepts for the theory of evaluation: the aggregative operator. Eur. J. Oper. Res. 10, 282–293 (1982)

    Article  MathSciNet  MATH  Google Scholar 

  6. Dubois, D., Prade, H.: A review of fuzzy set aggregation connectives. Inf. Sci. 36, 85–121 (1985)

    Article  MathSciNet  MATH  Google Scholar 

  7. Dubois, D., Prade, H.: Possibility Theory: An Approach to Computerized Processing of Uncertainty. Plenum Press, New York (1988)

    Book  MATH  Google Scholar 

  8. Dyckhoff, H., Pedrycz, W.: Generalized means as model of compensative connectives. Fuzzy Sets Syst. 14, 143–154 (1984)

    Article  MathSciNet  MATH  Google Scholar 

  9. Grabisch, M.: Fuzzy integrals in multicriteria decision making. Fuzzy Sets Syst. 69, 279–298 (1995)

    Article  MathSciNet  MATH  Google Scholar 

  10. Grabisch, M., Nguyen, H.T., Walker, E.A.: Fundamentals of Uncertainty Calculi With Applications to Fuzzy Inference, B: Mathematical and Statistical Methods, vol. 30. Kluwer Academic Publihers, Dordrecht (1995)

    Book  Google Scholar 

  11. Hardy, G.H., Littlewood, J.E., Polya, G.: Inequalities, 2nd edn. Cambridge University Press, London (1973)

    MATH  Google Scholar 

  12. Kaymak, U.: Fuzzy decision making with control applications. Ph.D. thesis, Delft University of Technology, P.O. Box 5031, 2600 GA, Delft, the Netherlands (1998)

    Google Scholar 

  13. Kaymak, U., van Nauta Lemke, H.R.: A sensitivity analysis approach to introducing weight factors into decision functions in fuzzy multicriteria decision making. Fuzzy Sets Syst. 97(2), 169–182 (1998)

    Google Scholar 

  14. Kim, K., Park, K.S.: Ranking fuzzy numbers with index of optimism. Fuzzy Sets Syst. 35, 143–150 (1990)

    Article  MathSciNet  Google Scholar 

  15. Klement, E.P.: Operations on fuzzy setsan axiomatic approach. Inf. Sci. 27(3), 221–232 (1982)

    Google Scholar 

  16. Klir, G.J., Folger, T.A.: Fuzzy Sets, Uncertainty and Information. Prentice-Hall, New Jersey (1988)

    MATH  Google Scholar 

  17. Kovalerchuk, B., Taliansky, V.: Comparison of empirical and computed values of fuzzy conjunction. Fuzzy Sets Syst. 46, 49–53 (1992)

    Article  Google Scholar 

  18. Krishnapuram, R., Lee, J.: Fuzzy-connective-based hierarchical aggregation networks for decision making. Fuzzy Sets Syst. 46, 11–27 (1992)

    Article  MathSciNet  Google Scholar 

  19. Luce, R.D., Raiffa, H.: Games and Decisions. John Wiley, New York (1957)

    MATH  Google Scholar 

  20. Mizumoto, M.: Pictorial representations of fuzzy connectives, part I: cases of t-norms, t-conorms and averaging operators. Fuzzy Sets Syst. 31, 217–242 (1989)

    Article  MathSciNet  Google Scholar 

  21. Mizumoto, M.: Pictorial representations of fuzzy connectives, part II: cases of compensatory operators and self-dual operators. Fuzzy Sets Syst. 32, 45–79 (1989)

    Article  MathSciNet  MATH  Google Scholar 

  22. Ovchinnikov, S.: On robust aggregation procedures. In: Buchon-Meunier, B. (ed.) Aggregation and Fusion of Imperfect Information, Studies in Fuzziness and Soft Computing, vol. 12, pp. 3–10. Springer, Heidelberg (1998)

    Chapter  Google Scholar 

  23. Thole, U., Zimmermann, H.J., Zysno, P.: On the suitability of minimum and product operators for the intersection of fuzzy sets. Fuzzy Sets Syst. 2, 167–180 (1979)

    Article  MATH  Google Scholar 

  24. van Nauta Lemke, H.R., Dijkman, J.G., van Haeringen, H., Pleeging, M.: A characteristic optimism factor in fuzzy decision-making. In: Proceedings of IFAC Symposium on Fuzzy Information, Knowledge Representation and Decision Analysis, pp. 283–288. Marseille, France (1983)

    Google Scholar 

  25. Yager, R.R.: Fuzzy decision making including unequal objectives. Fuzzy Sets Syst. 1, 87–95 (1978)

    Article  MATH  Google Scholar 

  26. Yager, R.R.: A measurement-informational discussion of fuzzy union and intersection. Int. J. Man-Mach. Stud. 11, 189–200 (1979)

    Article  MathSciNet  MATH  Google Scholar 

  27. Yager, R.R.: On a general class of fuzzy connectives. Fuzzy Sets Sys. 4, 235–242 (1980)

    Article  MathSciNet  MATH  Google Scholar 

  28. Yager, R.R.: On ordered weighted averaging aggregation operators in multicriteria decisionmaking. IEEE Trans. Syst. Man Cybern. 18(1), 183–190 (1988)

    Article  MathSciNet  MATH  Google Scholar 

  29. Zadeh, L.A.: Outline of a new approach to the analysis of complex systems and decision processes. IEEE Trans. Syst. Man Cybern. 3, 28–44 (1973)

    Article  MathSciNet  MATH  Google Scholar 

  30. Zimmermann, H.J.: Results of empirical studies in fuzzy set theory. In: Klir, G.J. (ed.) Applied General Systems Research: Recent Developments, pp. 303–312. Plenum Press, New York (1978)

    Chapter  Google Scholar 

  31. Zimmermann, H.J.: Fuzzy Sets, Decision Making and Expert Systems. Kluwer Academic Publishers, Boston (1987)

    Book  Google Scholar 

  32. Zimmermann, H.J.: Fuzzy Set Theory and its Application, 3rd edn. Kluwer, Boston (1996)

    Book  MATH  Google Scholar 

  33. Zimmermann, H.J., Zysno, P.: Latent connectives in human decision making. Fuzzy Sets Syst. 4, 37–51 (1980)

    Article  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Industrial Engineering, Eindhoven University of Technology, P.O. Box 513, 5600 MB, Eindhoven, The Netherlands

    Uzay Kaymak

Authors
  1. Uzay Kaymak
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Uzay Kaymak .

Editor information

Editors and Affiliations

  1. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

  2. Research and Innovation Center, Ford Motor Company, Dearborn, Michigan, USA

    Dimitar Filev

  3. Deakin University, Burwood, Victoria, Australia

    Gleb Beliakov

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Kaymak, U. (2017). On Practical Applicability of the Generalized Averaging Operator in Fuzzy Decision Making. In: Kacprzyk, J., Filev, D., Beliakov, G. (eds) Granular, Soft and Fuzzy Approaches for Intelligent Systems. Studies in Fuzziness and Soft Computing, vol 344. Springer, Cham. https://doi.org/10.1007/978-3-319-40314-4_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-40314-4_6

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-40312-0

  • Online ISBN: 978-3-319-40314-4

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation