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Group Decision Making: Consensus Approaches Based on Soft Consensus Measures

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Fuzzy Sets, Rough Sets, Multisets and Clustering

Part of the book series: Studies in Computational Intelligence ((SCI,volume 671))

Abstract

A group decision making situation involves multiple decision makers communicating with others to reach a decision. In such a situation, the most important issue is to obtain a decision that is best acceptable by the decision makers, and, therefore, consensus has attained a great attention and it is a major goal of group decision making situations. To measure the closeness among the opinions given by the decision makers, different approaches have been proposed. At the beginning, consensus was meant to be a unanimous and full agreement. However, because this situation is often not reachable in practice, the use of a softer consensus, which assesses the level of agreement in a more flexible way and reflects the large spectrum of possible partial agreements, is a more reasonable approach. Soft consensus approaches better reflects a real human perception of the essence of consensus and, therefore, they have been widely used. The purpose of this contribution is to review the different consensus approaches based on soft consensus measures that have been proposed.

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References

  1. Alonso, S., Pérez, I.J., Cabrerizo, F.J., Herrera-Viedma, E.: A linguistic consensus model for web 2.0 communities. Applied Soft Computing 13(1), 149–157 (2013)

    Article  Google Scholar 

  2. Ben-Arieh, D., Chen, Z.: Linguistic-labels aggregation and consensus measure for autocratic decision making using group recommendations. IEEE Transactions on Systems Man and Cybernetics - Part A: Systems and Humans 36(3), 558–568 (2006)

    Article  Google Scholar 

  3. Bezdek, J., Spillman, B., Spillman, R.: A fuzzy relation space for group decision theory. Fuzzy Sets and Systems 1(4), 255–268 (1978)

    Article  MathSciNet  MATH  Google Scholar 

  4. Bryson, N.: Group decision-making and the analytic hierarchy process: Exploring the consensus-relevant information content. Computers & Operations Research 23(1), 27–35 (1996)

    Article  MATH  Google Scholar 

  5. Butler, C.T., Rothstein, A.: On conflict and consensus: A handbook on formal consensus decision making. Tahoma Park (2006)

    Google Scholar 

  6. Cabrerizo, F.J., Moreno, J.M., Pérez, I.J., Herrera-Viedma, E.: Analyzing consensus approaches in fuzzy group decision making: Advantages and drawbacks. Soft Computing 14(5), 451–463 (2010)

    Article  Google Scholar 

  7. Cabrerizo, F.J., Heradio, R., Pérez, I.J., Herrera-Viedma, E.: A selection process based on additive consistency to deal with incomplete fuzzy linguistic information. Journal of Universal Computer Science 16(1), 62–81 (2010)

    MathSciNet  MATH  Google Scholar 

  8. Cabrerizo, F.J., Pérez, I.J., Herrera-Viedma, E.: Managing the consensus in group decision making in an unbalanced fuzzy linguistic context with incomplete information. Knowledge-Based Systems 23(2), 169–181 (2010)

    Article  Google Scholar 

  9. Chen, S.J., Hwang, C.L.: Fuzzy multiple attributive decision making: Theory and its applications. Springer, Berlin (1992)

    Book  Google Scholar 

  10. Chen, X., Zhang, H., Dong, Y.: The fusion process with heterogeneous preference structures in group decision making: A survey. Information Fusion 24, 72–83 (2015)

    Article  Google Scholar 

  11. Chiclana, F., Herrera-Viedma, E., Herrera, F., Alonso, S.: Some induced ordered weighted averaging operators and their use for solving group decision making problems based on fuzzy preference relations. European Journal of Operational Research 182(1), 383–399 (2007)

    Article  MATH  Google Scholar 

  12. Coch, L., French, J.R.P.: Overcoming resistance to change. Human Relations 1(4), 512–532 (1948)

    Article  Google Scholar 

  13. Cutello, V., Montero, J.: Fuzzy rationality measures. Fuzzy Sets and Systems 62(1), 39–54 (1994)

    Article  MathSciNet  MATH  Google Scholar 

  14. Dubois, D., Prade, H., Testemale, C.: Weighted fuzzy pattern matching. Fuzzy Sets and Systems 28(3), 313–331 (1988)

    Article  MathSciNet  MATH  Google Scholar 

  15. Dubois, D., Koning, J.L.: Social choice axioms for fuzzy set aggregation. Fuzzy Sets and Systems 43(3), 257–274 (1991)

    Article  MathSciNet  MATH  Google Scholar 

  16. 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 4(3), 313–327 (1988)

    Article  MATH  Google Scholar 

  17. Fedrizzi, M., Pasi, G.: Fuzzy logic approaches to consensus modeling in group decision making. In: Ruan, D., Hardeman, F., Van Der Meer, K. (Eds) Intelligent Decision and Policy Making Support Systems, pp. 19–37. Springer-Verlag, Berlin-Heidelberg (2008)

    Chapter  Google Scholar 

  18. French, J.R.P.: A formal theory of social power. Psychological Review 63(3), 181–194 (1956)

    Article  Google Scholar 

  19. Fodor, J., Roubens, M.: Fuzzy preference modeling and multicriteria decision support. Kluwer, Dordrecht (1994)

    Book  MATH  Google Scholar 

  20. Grabisch, M., Marichal, J.-L., Mesiar, R., Endre, P.: Aggregation functions (Encyclopedia of Mathematics and its Applications). Cambridge University Press, New York (2009)

    Book  MATH  Google Scholar 

  21. Grabisch, M., Labreuche, C.: Fuzzy measures and integrals in MCDA. In: Greco, S., Ehrgott, M., Figueira, J.R. (Eds) Multiple Criteria Decision Analysis, pp. 553–603. Springer, New York (2016)

    Chapter  Google Scholar 

  22. Harary, F.: On the measurement of structural balance. Behavioral Science 4(4), 316–323 (1959)

    Article  MathSciNet  Google Scholar 

  23. Herrera, F., Herrera-Viedma, E., Verdegay, J.L.: A model of consensus in group decision making under linguistic assessments. Fuzzy Sets and Systems 78(1), 73–87 (1996)

    Article  MathSciNet  MATH  Google Scholar 

  24. Herrera, F., Herrera-Viedma, E., Verdegay, J.L.: A rational consensus model in group decision making using linguistic assessments. Fuzzy Sets and Systems 88(1), 31–49 (1997)

    Article  MATH  Google Scholar 

  25. Herrera, F., Herrera-Viedma, E., Verdegay, J.L.: Linguistic measures based on fuzzy coincidence for reaching consensus in group decision making. International Journal of Approximate Reasoning 16(3–4), 309–334 (1997)

    Article  MATH  Google Scholar 

  26. Herrera, F., Herrera-Viedma, E.: Linguistic decision analysis: Steps for solving decisions problems under linguistic information. Fuzzy Sets and Systems 115(1), 67–82 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  27. Herrera, F., Alonso, S., Chiclana, F., Herrera-Viedma, E.: Computing with words in decision making: Foundations, trends and prospects. Fuzzy Optimization and Decision Making 8(4), 337–364 (2009)

    Article  MATH  Google Scholar 

  28. Herrera-Viedma, E., Herrera, F., Chiclana, F.: A consensus model for multiperson decision making with different preference structures. IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans 32(3), 394–402 (2002)

    Article  MATH  Google Scholar 

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

    Article  Google Scholar 

  30. Herrera-Viedma, E., Herrera, F., Alonso, S.: Group decision-making model with incomplete fuzzy preference relations based on additive consistency. IEEE Transactions on Systems, Man and Cybernetics - Part B: Cybernetics 37(1), 176–189 (2007)

    Article  MATH  Google Scholar 

  31. Herrera-Viedma, E., Cabrerizo, F.J., Kacprzyk, J., Pedrycz, W.: A review of soft consensus models in a fuzzy environment. Information Fusion 17, 4–13 (2014)

    Article  Google Scholar 

  32. Kacprzyk, J.: Group decision-making with a fuzzy majority via linguistic quantifiers. Part I: A consensory-like pooling. Cybernetics and Systems: An International Journal 16(2–3), 119–129 (1985)

    MATH  Google Scholar 

  33. Kacprzyk, J.: Group decision-making with a fuzzy majority via linguistic quantifiers. Part I: A competitive-like pooling. Cybernetics and Systems: An International Journal 16(2–3), 131–144 (1985)

    MATH  Google Scholar 

  34. Kacprzyk, J.: Group decision making with a fuzzy linguistic majority. Fuzzy Sets and Systems 18(2), 105–118 (1986)

    Article  MathSciNet  MATH  Google Scholar 

  35. Kacprzyk, J.: On some fuzzy cores and ‘soft’ consensus measures in group decision making. In: Bezdek, J.C. (Ed) The Analysis of Fuzzy Information, pp. 119–130. CRC Press, Boca Raton (1987)

    Google Scholar 

  36. Kacprzyk, J., Fedrizzi, M.: A ‘soft’ measure of consensus in the setting of partial (fuzzy) preferences. European Journal of Operational Research 34(3), 316–325 (1988)

    Article  MathSciNet  Google Scholar 

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

    Article  MathSciNet  MATH  Google Scholar 

  38. Kacprzyk, J., Fedrizzi, M., Nurmi, H.: Group decision making and consensus under fuzzy preferences and fuzzy majority. Fuzzy Sets and Systems 49(1), 21–31 (1992)

    Article  MathSciNet  MATH  Google Scholar 

  39. Kacprzyk, J., Zadrozny, S., Ras, Z.W.: How to support consensus reaching using action rules: a novel approach. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 18(4), 451–470 (2010)

    Article  MathSciNet  Google Scholar 

  40. Loewer, B.: Special issue on consensus. Synthese 62(1), 1–122 (1985)

    Article  MathSciNet  Google Scholar 

  41. Loewer, B., Laddaga, R.: Destroying the consensus. Synthese 62(1), 79–96 (1985)

    Article  Google Scholar 

  42. Mata, F., Martinez, L., Herrera-Viedma, E.: An adaptive consensus support model for group decision-making problems in a multigranular fuzzy linguistic context. IEEE Transactions on Fuzzy Systems 17(2), 279–290 (2009)

    Article  Google Scholar 

  43. Narukawa, Y., Torra, V.: Fuzzy measures and integrals in evaluation of strategies. Information Sciences 177(21), 4686–4695 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  44. Orlovski, S.A.: Decision-making with a fuzzy preference relation. Fuzzy Sets and Systems 1(3), 155–167 (1978)

    Article  MathSciNet  Google Scholar 

  45. Pawlak, A.: Information systems theoretical foundations. Information Systems 6(3), 205–218 (1981)

    Article  MATH  Google Scholar 

  46. Pérez, I.J., Cabrerizo, F.J., Alonso, S., Herrera-Viedma, E.: A new consensus model for group decision making problems with non homogeneous experts. IEEE Transactions on Systems, Man, and Cybernetics: Systems 44(4), 494–498 (2014)

    Article  Google Scholar 

  47. Pérez, L.G., Mata, F., Chiclana, F., Kou, G., Herrera-Viedma, E.: Modeling influence in group decision making. Soft Computing 20(4), 1653–1665 (2016)

    Article  Google Scholar 

  48. Roubens, M.: Fuzzy sets and decision analysis. Fuzzy Sets and Systems 90(2), 199–206 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  49. Saaty, T.L.: The analytic hierarchy process: Planning, priority setting, resource allocation. McGraw-Hill, New York (1980)

    MATH  Google Scholar 

  50. Saint, S., Lawson, J.R.: Rules for reaching consensus: A modern approach to decision making. Jossey-Bass (1994)

    Google Scholar 

  51. Spillman, B., Bezdek, J., Spillman, R.: Coalition analysis with fuzzy sets. Kybernetes 8(3), 203–211 (1979)

    Article  MATH  Google Scholar 

  52. Tanino, T.: Fuzzy preference orderings in group decision making. Fuzzy Sets and Systems 12(2), 117–131 (1984)

    Article  MathSciNet  MATH  Google Scholar 

  53. Torra, V., Narukawa, Y.: Modeling decisions: Information fusion and aggregation operators. Springer-Verlag (2007)

    Google Scholar 

  54. Yager, R.R.: On ordered weighted averaging aggregation operators in multicriteria decision making. IEEE Transactions on Systems Man and Cybernetics 18(1), 183–190 (1988)

    Article  MathSciNet  MATH  Google Scholar 

  55. Zadeh, L.A.: Fuzzy sets. Information and Control 8(3), 338–353 (1965)

    Article  MathSciNet  MATH  Google Scholar 

  56. Zadeh, L.A.: A computational approach to fuzzy quantifiers in natural languages. Computers & Mathematics with Applications 9(1), 149–184 (1983)

    Article  MathSciNet  MATH  Google Scholar 

  57. Zadrozny, S., Kacprzyk, J.: Issues in the practical use of the OWA operators in fuzzy querying. Journal of Intelligent Information Systems 33(3), 307–325 (2009)

    Article  Google Scholar 

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Acknowledgements

The authors would like to acknowledge FEDER financial support from the Project TIN2013-40658-P, and also the financial support from the Andalusian Excellence Project TIC-5991.

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Authors and Affiliations

  1. Department of Computer Sciences and Artificial Intelligence, University of Granada, C/ Periodista Daniel Saucedo Aranda S/n, 18071, Granada, Spain

    Francisco Javier Cabrerizo & Enrique Herrera-Viedma

  2. Department of Computer Sciences and Engineering, University of Cádiz, Avenida Universidad de Cádiz 10, 11519, Puerto Real, Spain

    Ignacio Javier Pérez

  3. Faculty of Technology, Centre for Computational Intelligence, De Montfort University, Leicester, LE1 9BH, UK

    Francisco Chiclana

Authors
  1. Francisco Javier Cabrerizo
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  2. Ignacio Javier Pérez
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  3. Francisco Chiclana
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  4. Enrique Herrera-Viedma
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Corresponding author

Correspondence to Francisco Javier Cabrerizo .

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Editors and Affiliations

  1. University of Skövde, School of Informatics University of Skövde, Skövde, Sweden

    Vicenç Torra

  2. University of Skövde, School of Informatics University of Skövde, Skövde, Sweden

    Anders Dahlbom

  3. Toho Gakuen , Tokyo, Japan

    Yasuo Narukawa

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Cabrerizo, F.J., Pérez, I.J., Chiclana, F., Herrera-Viedma, E. (2017). Group Decision Making: Consensus Approaches Based on Soft Consensus Measures. In: Torra, V., Dahlbom, A., Narukawa, Y. (eds) Fuzzy Sets, Rough Sets, Multisets and Clustering. Studies in Computational Intelligence, vol 671. Springer, Cham. https://doi.org/10.1007/978-3-319-47557-8_18

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  • DOI: https://doi.org/10.1007/978-3-319-47557-8_18

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