Abstract
In Group Decision Making (GDM) the automatic consensus models are guided by different consensus measures which usually are obtained by aggregating similarities observed among experts' opinions. Most GDM problems based on linguistic approaches use symmetrically and uniformly distributed linguistic term sets to express experts' opinions.However, there exist problemswhose assessments need to be represented by means of unbalanced linguistic term sets, i.e., using term sets which are not uniformly and symmetrically distributed. The aim of this paper is to present different Linguistic OWA Operators to compute the consensus measures in consensusmodels for GDMproblems with unbalanced fuzzy linguistic information. © 2011 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
Herrera-Viedma, E., Cabrerizo, F. J., Pérez, I. J., Cobo, M. J., Alonso, S., & Herrera, F. (2011). Applying linguistic OWA operators in consensus models under unbalanced linguistic information. Studies in Fuzziness and Soft Computing (Vol. 265, pp. 167–186). Springer Verlag. https://doi.org/10.1007/978-3-642-17910-5_9
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