Abstract
This paper presents a probabilistic model for linguistic multi-expert decision making (MEDM), which is able to deal with vague concepts in linguistic aggregation and decision-makers’ preference information in choice function. In linguistic aggregation phase, the vagueness of each linguistic judgement is captured by a possibility distribution on a set of linguistic labels. A confidence parameter is also incorporated into the basic model to model experts’ confidence degree. The basic idea of this linguistic aggregation is to transform a possibility distribution into its associated probability distribution. The proposed linguistic aggregation results in a set of labels having a probability distribution. As a choice function, a target-oriented ranking method is proposed, which implies that the decision-maker is satisfactory to choose an alternative as the best if its performance is as at least “good” as his requirements.
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References
Ben-Arieh, D., Chen, Z.: On linguistic labels aggregation and consensus measure for autocratic decision-making using group recommendations. IEEE T. Syst. Man Cy 36(2), 558–568 (2006)
Bordley, R., LiCalzi, M.: Decision analysis using targets instead of utility functions. Decis. Econ. Finan. 23(1), 53–74 (2000)
Bordogna, G., Fedrizzi, M., Passi, G.: A linguistic modeling of consensus in group decision making based on OWA operator. IEEE T. Syst. Man Cy. 27(1), 126–132 (1997)
Degani, R., Bortolan, G.: The problem of linguistic approximation in clinical decision making. Int. J. Approx. Reason 2(2), 143–162 (1988)
Delgado, M., Verdegay, J.L., Vila, M.A.: On aggregation operations of linguistic labels. Int. J. Intell. Syst. 8(3), 351–370 (1993)
Dubois, D., Nguyen, H.T., Prade, H.: Possibility theory, probability and fuzzy sets: Misunderstandings, bridges and gaps. In: Dubois, D., Prade, H. (eds.) Fundamentals of Fuzzy Sets. Mass, pp. 343–438. Kluwer, Boston (2000)
Herrera, F., Martínez, L.: A 2-tuple fuzzy linguistic representation model for computing with words. IEEE T. Fuzzy Syst. 8(6), 746–752 (2000)
Herrera-Viedma, E., Herrera, F., Chiclana, F.: A consensus model for multiperson decision making with different preference structures. IEEE T. Syst. Man Cy. 32(3), 394–402 (2002)
Huynh, V.-N., Nakamori, Y.: A satisfactory-oriented approach to multi-expert decision-making with linguistic assessments. IEEE T. Syst. Man Cy. 35(2), 184–196 (2005)
Lawry, J.: A methodology for computing with words. Int. J. Approx. Reason 28(2–3), 51–89 (2001)
Lawry, J.: A framework for linguistic modelling. Artif. Intell. 155(1–2), 1–39 (2004)
Lawry, J.: Appropriateness measures: An uncertainty model for vague concepts. Synthese 161(2), 255–269 (2008)
Lawry, J., Tang, Y.: Uncertainty modelling for vague concepts: A prototype theory approach. Artif. Intell. 173(18), 1539–1558 (2009)
Savage, L.J.: The Foundations of Statistics. Wiley, New York (1954)
Shanteau, J.: What does it mean when experts disagree? In: Salas, E., Klein, G.A. (eds.) Linking Expertise and Naturalistic Decision Making, pp. 229–244. Psychology Press, USA (2001)
Simon, H.A.: A behavioral model of rational choice. Qual. J. Econ. 69(1), 99–118 (1955)
Tang, Y.: A collective decision model involving vague concepts and linguistic expressions. IEEE T. Syst. Man Cy. 38(2), 421–428 (2008)
Tang, Y., Zheng, J.: Linguistic modelling based on semantic similarity relation among linguistic labels. Fuzzy Set Syst. 157(12), 1662–1673 (2006)
Zadeh, L.A.: The concept of a linguistic variable and its application to approximate reasoning. Inform Sciences Part I 8(3), 199–249, Part II 8(4), 301–357, Part III 9(1), 43–80 (1975)
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Yan, HB., Huynh, VN., Nakamori, Y. (2010). Linguistic Multi-Expert Decision Making Involving Semantic Overlapping. In: Huynh, VN., Nakamori, Y., Lawry, J., Inuiguchi, M. (eds) Integrated Uncertainty Management and Applications. Advances in Intelligent and Soft Computing, vol 68. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11960-6_26
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DOI: https://doi.org/10.1007/978-3-642-11960-6_26
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