A model based on linguistic 2-tuples for dealing with multigranular hierarchical linguistic contexts in multi-expert decision-making

In those problems that deal with multiple sources of linguistic information we can find problems defined in contexts where the linguistic assessments are assessed in linguistic term sets with different granularity of uncertainty and/or semantics (multi-granular linguistic contexts). Different approaches have been developed to manage this type of contexts [1], [2], that unify the multi-granular linguistic information in an unique linguistic term set for an easy management of the information, This normalization process can produce a loss of information and hence a lack of precision in the final results. In this paper, we shall present a type of multi-granular linguistic contexts we shall call linguistic hierarchies term sets, such that, when we deal with multi-granular linguistic information assessed in these structures we can unify the information assessed in them without loss of information. To do so, we shall use the 2-tuple linguistic representation model [3], [4]. Afterwards we shall develop a linguistic decision model dealing with multi-granular linguistic contexts and apply it to a multi- expert decision-making problem.