Attitude-Based Consensus Model for Heterogeneous Group Decision Making

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 214)


Usually, human beings make decisions in their daily life providing their preferences according to their knowledge area and background. Therefore, when a high number of decision makers take part in a group decision-making problem, it is usual that they use different information domains to express their preferences. Besides, it might occur that several subgroups of decision makers have different interests, which may lead to situations of disagreement amongst them. Therefore, the integration of the group’s attitude toward consensus might help optimizing the consensus reaching process according to the needs of decision makers. In this contribution, we propose an attitude-based consensus model for heterogeneous group decision-making problems with large groups of decision makers.


Group decision making Heterogeneous information Attitude Consensus reaching 



This work is partially supported by the Research Project TIN-2009-08286 and FEDER funds.


  1. 1.
    Herrera F, Herrera-Viedma E (2000) Linguistic decision analysis: steps for solving decision problems under linguistic information. Fuz Sets and Sys 115:67–82MathSciNetCrossRefMATHGoogle Scholar
  2. 2.
    Herrera F, Martínez L, Sánchez PJ (2005) Managing non-homogeneous information in group decision making. Eur J Oper Res 166(1):115–132CrossRefMATHGoogle Scholar
  3. 3.
    Kacprzyk J (1986) Group decision making with a fuzzy linguistic majority. Fuzzy Sets Syst 18(2):105–118MathSciNetCrossRefMATHGoogle Scholar
  4. 4.
    Kim J (2008) A model and case for supporting participatory public decision making in e-democracy. Group Decis Negot 17(3):179–192CrossRefGoogle Scholar
  5. 5.
    Li DF, Huang ZG, Chen GH (2010) A systematic approach to heterogeneous multiattribute group decision making. Comput Ind Eng 59(4):561–572MathSciNetCrossRefGoogle Scholar
  6. 6.
    Palomares I, Liu J, Xu Y, Martínez L (2012) Modelling experts’ attitudes in group decision making. Soft Comput 16(10):1755–1766CrossRefMATHGoogle Scholar
  7. 7.
    Palomares I, Rodríguez RM, Martínez L (2013) An attitude-driven web consensus support system for heterogeneous group decision making. Expert Syst Appl 40(1):139–149CrossRefGoogle Scholar
  8. 8.
    Saint S, Lawson JR (1994) Rules for reaching consensus. A modern approach to decision making. Jossey-Bass, San FranciscoGoogle Scholar
  9. 9.
    Sueur C, Deneubourg JL, Petit O (2012) From social network (centralized vs. decentralized) to collective decision-making (unshared vs. shared consensus). PLoS one 7(2):1–10CrossRefGoogle Scholar
  10. 10.
    Yager RR (1988) On orderer weighted averaging aggregation operators in multi-criteria decision making. IEEE Trans Syst Man Cyber 18(1):183–190MathSciNetCrossRefMATHGoogle Scholar
  11. 11.
    Yager RR (1996) Quantifier guided aggregation using OWA operators. Int J Intell Syst 11:49–73CrossRefGoogle Scholar
  12. 12.
    L.A. Zadeh (1975) The concept of a linguistic variable and its applications to approximate reasoning. Inf Sci Part I, II, III, 8,8,9:199–249,301–357,43–80Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversity of JaénJaénSpain

Personalised recommendations