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Towards a New Generation of Indicators for Consensus Reaching Support Using Type-2 Fuzzy Sets

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Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications (IPMU 2010)

Abstract

In this paper, we consider group decision making setting and propose a novel concept of indicators which are meant to guide the discussion in the group that should lead to consensus. Preferences of the group members are assumed to be fuzzy sets of options. The proposed indicators help analyze the structure of preferences in the group. Their derivation is expressed as an optimization problem. The preferences of a member of the group are finally represented as type-2 fuzzy sets (and interval-valued fuzzy sets, in particular). It is shown that this higher order construct plays a pivotal role in the quantification of variability present in the preferences of the group members. We introduce a constructive way of estimation of type-2 membership functions by invoking a principle of justifiable granularity.

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References

  1. Kacprzyk, J., Zadrożny, S.: Soft computing and Web intelligence for supporting consensus reaching. Soft Computing 14(8), 833–846 (2010)

    Article  Google Scholar 

  2. Türksen, I.B.: Type 2 representation and reasoning for CWW. Fuzzy Sets and Systems 127, 17–36 (2002)

    Article  MATH  MathSciNet  Google Scholar 

  3. Mendel, J.M.: On answering the question, Where do I start in order to solve a new problem involving interval type-2 fuzzy sets? Information Sciences 179(19), 3418–3431 (2009)

    Article  MATH  MathSciNet  Google Scholar 

  4. Zhou, S.M., Chiclana, F., John, R.I., Garibaldi, J.M.: Type-1 OWA operators for aggregating uncertain information with uncertain weights induced by type-2 linguistic quantifiers. Fuzzy Sets and Systems 159(24), 3281–3296 (2008)

    Article  MATH  MathSciNet  Google Scholar 

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

    Article  MathSciNet  Google Scholar 

  6. Kacprzyk, J., Fedrizzi, M.: A ‘human-consistent’ degree of consensus based on fuzzy login with linguistic quantifiers. Mathematical Social Sciences 18(3), 275–290 (1989)

    Article  MATH  MathSciNet  Google Scholar 

  7. Zadrożny, S., Kacprzyk, J.: An internet-based group decision and consensus reaching support system. In: Yu, X., Kacprzyk, J. (eds.) Applied Decision Support with Soft Computing, pp. 263–275. Springer, Heidelberg (2003)

    Google Scholar 

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

    Google Scholar 

  9. Herrera-Viedma, E., Martinez, L., Mata, F., Chiclana, F.: A consensus support system model for group decision-making problems with multi-granular linguistic preference relations. IEEE Trans. on Fuzzy Systems 13(5), 644–658 (2005)

    Article  Google Scholar 

  10. Herrera-Viedma, E., Mata, F., Martınez, L., Perez, L.G.: An adaptive module for the consensus reaching process in group decision making problems. In: Torra, V., Narukawa, Y., Miyamoto, S. (eds.) MDAI 2005. LNCS (LNAI), vol. 3558, pp. 89–98. Springer, Heidelberg (2005)

    Google Scholar 

  11. Cholewa, W.: Aggregation of fuzzy opinions - an axiomatic approach. Fuzzy Sets and Systems 17, 249–258 (1985)

    Article  MATH  MathSciNet  Google Scholar 

  12. Montero de Juan, F.J.: Aggregation of fuzzy opinion in a non-homogeneous group. Fuzzy Sets and Systems 25, 15–20 (1987)

    MathSciNet  Google Scholar 

  13. Dubois, D., Koning, J.-L.: Social choice axioms for fuzzy set aggregation. Fuzzy Sets and Systems 43, 257–274 (1991)

    Article  MATH  MathSciNet  Google Scholar 

  14. Fung, L.W., Fu, K.S.: An axiomatic approach to rational decision making in a fuzzy environment. In: Zadeh, L., Fu, K.S., Tanaka, T., Shimura, M. (eds.) Fuzzy Sets and Their Applications to Cognitive and Decision Processes, pp. 227–256. Academic Press, New York (1975)

    Google Scholar 

  15. Dubois, D., Prade, H.: A review of fuzzy set aggregation connectives. Information Sciences 36, 85–121 (1985)

    Article  MATH  MathSciNet  Google Scholar 

  16. Choudhury, A.K., Shankar, R., Tiwari, M.K.: Consensus-based intelligent group decision-making model for the selection of advanced technology. Decision Support Systems 42(3), 1776–1799 (2006)

    Article  Google Scholar 

  17. Herrera, F., Martínez, L., Sánchez, P.J.: Managing non-homogeneous information in group decision making. European Journal of Operational Research 166(1), 115–132 (2005)

    Article  MATH  Google Scholar 

  18. Tiryaki, F., Ahlatcioglu, B.: Fuzzy portfolio selection using fuzzy analytic hierarchy process. Information Sciences 179(1-2), 53–69 (2009)

    Article  MATH  Google Scholar 

  19. Tsabadze, T.: A method for fuzzy aggregation based on group expert evaluations. Fuzzy Sets and Systems 157(10), 1346–1361 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  20. Bargiela, A., Pedrycz, W.: Granular Computing. An Introduction. Springer, Heidelberg (2002)

    Google Scholar 

  21. Pedrycz, W.: Granular computing in multi-agent systems. In: Wang, G., Li, T., Grzymala-Busse, J.W., Miao, D., Skowron, A., Yao, Y. (eds.) RSKT 2008. LNCS (LNAI), vol. 5009, pp. 3–17. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

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Pedrycz, W., Kacprzyk, J., Zadrożny, S. (2010). Towards a New Generation of Indicators for Consensus Reaching Support Using Type-2 Fuzzy Sets. In: Hüllermeier, E., Kruse, R., Hoffmann, F. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications. IPMU 2010. Communications in Computer and Information Science, vol 81. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14058-7_24

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  • DOI: https://doi.org/10.1007/978-3-642-14058-7_24

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14057-0

  • Online ISBN: 978-3-642-14058-7

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