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A Fusion Method for Multi-granularity Linguistic Information Based on the 2-tuple Fuzzy Linguistic Representation Model a Fusion Method for Multi-granularity Linguistic Information Based on the 2-tuple Fuzzy Linguistic Representation Model

The Fuzzy Linguistic Approach has been applied successfully to many problems dealing with qualitative aspects that are assessed by means of linguistic terms. The use of linguistic information implies in most cases the need for using fusion processes to obtain aggregated values that summarize the input information. One important limitation of the fuzzy linguistic approach appears when fusion processes are applied to problems in which the linguistic information is assessed in linguistic term sets with diierent granularity of uncertainty, i.e., diierent cardinality; this type of information is denoted as multi-granularity linguistic information. This limitation consists of the diiculty in dealing with this type of information in fusion processes due to the fact that there is no standard normalization process for this type of information, as in the numerical domain. In this contribution, taking as the base the 2-tuple fuzzy linguistic representation model and its computational technique, we shall present a method for easily dealing with multi-granularity linguistic information in fusion processes. Afterwards, we shall apply this fusion method to a decision process in a multi-expert decision-making problem with multi-granularity linguistic information.