Un modelo de consenso para problemas de toma de decisiones multicriterio en grupo mediante relaciones de preferencia intervalares difusas lingüísticas

  1. Tapia García, Juan Miguel
  2. Moral Ávila, María José del
  3. Tapia García, Cristóbal
  4. Martínez, María Ángeles
  5. Amor Pulido, Raúl
Revista:
Revista de métodos cuantitativos para la economía y la empresa

ISSN: 1886-516X

Año de publicación: 2012

Volumen: 14

Páginas: 36-53

Tipo: Artículo

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Otras publicaciones en: Revista de métodos cuantitativos para la economía y la empresa

Resumen

In some circumstances a decision maker, expert, in a group decision making problem cannot express his/her preferences with a unique linguistic fuzzy preference because he/she is dubious into some preferences. In this paper, we present a consensus model for group decision making problems with interval fuzzy preference relations. This model is based on two consensus criteria, a consensus measure and a proximity measure, and on the concept of coincidence among preferences. We compute both consensus criteria in the three representation levels of a preference relation and design an automatic feedback mechanism to guide experts in the consensus reaching process.

Referencias bibliográficas

  • Alonso, S.; Herrera-Viedma, E.; Chiclana, F.; Herrera, F. (2010). A Web Based Consensus Support System for Group Decision Making Problems and Incomplete Preferences. Information Sciences, 180:23 (2010), 4477-4495.
  • Bustince, H.; Fernandez, J.; Sanz, J.; Galar, M.; Mesiar, R. (2012). Multicriteria decision making by means of interval-valued Choquet integrals. Advances in Intelligent and Soft Computing, 107, 269-278.
  • Cabrerizo, F.J.; López-Gijón, J.; Ruíz-Rodríguez, A.A.; Herrera-Viedma, E. (2010a). A Model Based on Fuzzy Linguistic Information to Evaluate the Quality of Digital Libraries. Int. J. Inform. Technol. Decis. Making 9:3, 455-472.
  • Cabrerizo, F.J.; Moreno, J.M.; Pérez, I.J.; Herrera-Viedma, E. (2010b). Analyzing consensus approaches in fuzzy group decision making: advantages and drawbacks. Soft Computing 14:5, 451-463.
  • Cabrerizo, F.J.; Pérez, I.J.; Herrera-Viedma, E. (2010c). Managing the Consensus in Group Decision Making in an Unbalanced Fuzzy Linguistic Context with Incomplete Information. Knowledge-Based Systems 23:2,169-181.
  • Chiclana, F.; Herrera, F.; Herrera-Viedma, E. (1998). Integrating three representation models in fuzzy multipurpose decision making based on fuzzy preference relations. Fuzzy Sets and Systems, 97(1), 33-48.
  • Herrera, F.; Herrera-Viedma, E. (1997). Aggregation operators for linguistic weighted information. IEEE Trans. System Man Cybernet. 27, 646-656.
  • Herrera, F.; Herrera-Viedma, E. (2000). Linguistic decision analysis: steps for solving decision problems under linguistic information. Fuzzy Sets and Systems 115, 67-82.
  • Herrera, F.; Herrera-Viedma, E.; Verdegay, J.L. (1995). A sequential selection process in group decision making with linguistic assessment. Inform. Sci. 85, 223-239.
  • Herrera, F.; Herrera-Viedma, E.; Verdegay, J.L. (1996). A model of consensus in group decision making under linguistic assessments. Fuzzy Sets and Systems 78, 73-87.
  • Herrera, F.; Herrera-Viedma, E.; Verdegay, J.L. (1997a). A rational consensus model in group decision making under linguistic assessment. Fuzzy Sets and Systems 88,31-49.
  • Herrera, F.; Herrera-Viedma, E.; Verdegay, J.L. (1997b). Linguistic Measures Based on Fuzzy Coincidence for Reaching Consensus in Group Decision Making. International Journal of Approximate Reasoning 16, 309-334.
  • Herrera-Viedma, E.; Alonso, S.; Chiclana, F.; Herrera, F. (2007a). A consensus model for group decision making with incomplete fuzzy preference relations. IEEE Trans. Fuzzy Syst. 15, 863-877.
  • Herrera-Viedma, E.; Chiclana, F.; Herrera, F.; Alonso, S. (2007b). 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.
  • Herrera-Viedma, E.; Herrera, F.; Chiclana, F. (2002). A consensus model for multiperson decision making with different preference structures. IEEE Transactions on Systems Man and Cybernetics Part A - Systems and Humans 32, 394-402.
  • Herrera-Viedma, E.; Martínez, L.; Mata, F.; Chiclana, F. (2005). A consensus support system model for group decision-making problems with multi-granular linguistic preference relations. IEEE Trans. Fuzzy Syst. 13, 644-645.
  • Jiang Y. (2007). An approach to group decision making based on interval fuzzy preference relations. Journal of Systems Science and Systems Engineering, 16:1, 113-120.
  • Kacprzyk, J. (1987). On some fuzzy cores and "soft" consensus measures in group decision making, en The Analysis of Fuzzy Information (J. Bezdek Ed.). CRC Press, 119-130.
  • Kacprzyk, J.; Fedrizzi, M. (1986). "Soft" consensus measure for monitoring real consensus reaching processes under fuzzy preferences. Control Cybernet. 15, 309-323.
  • Kacprzyk, J.; Fedrizzi, M. (1988). A "soft" measure of consensus in the setting of partial (fuzzy) preferences. European J. Oper. Res. 34, 316-323.
  • Mata, F.; Martínez, L.; Herrera-Viedma, E. (2009). An adaptive consensus support model for group decision making problems in a multi-granular fuzzy linguistic context. IEEE Transactions on Fuzzy Systems, 17(2), 279-290.
  • Pérez, I.J.; Cabrerizo, F.J.; Herrera-Viedma, E. (2011). Group Decision Making Problems in a Linguistic and Dynamic Context. Expert Systems with Applications 38:3, 1675-1688.
  • Xu, Z.S. (2005). An approach to group decision making based on incomplete linguistic preference relations. International Journal of Information Technology and Decision Making 4(1), 153-160.
  • Xu, Z.S. (2007). A survey of preference relations. International Journal of General Systems 36, 179-203.
  • Xu, Z.S. (2010). Interactive group decision making procedure based on uncertain multiplicative linguistic preference relations. Journal of Systems Engineering and Electronics 21, 408-415.
  • Yager, R.R. (1988). On ordered weighted averaging aggregation operators in multicriteria decision making. IEEE Trans. Systems Man Cybernet. 18, 183-190.
  • Zadeh, L.A. (1975a). The concept of a linguistic variable and its applications to approximate reasoning. Part I. Information Sciences 8(3), 199-249.
  • Zadeh, L.A. (1975b). The concept of a linguistic variable and its applications to approximate reasoning. Part II. Information Sciences 8(4), 301-357.
  • Zadeh, L.A. (1975c). The concept of a linguistic variable and its applications to approximate reasoning. Part III. Information Sciences 9(1), 43-80.
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