2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC 2017)

134 / 2016-11-06 20:13:47

A new transformation algorithm for multi-granularity unbalanced linguistic terms

Multi-granularity; Unbalanced linguistic terms; 2-tuple linguistic model; Group decision making

The aim of this paper is to propose a transformation algorithm for multi-granularity linguistic information assessed in different unbalanced linguistic term sets together with its application in linguistic group decision making (LGDM) problem. Assuming that the linguistic information given to the alternatives by different decision-makers distribute in different granularity and/or semantic term sets. First, the transformation functions for linguistic preference information based on normalized accumulative area of triangle membership function and 2-tuple linguistic model are present to make linguistic information uniform, and then the linguistic transformation algorithm is proposed. Finally, an application of the proposed algorithm is introduced to illustrate the feasibility and effectiveness of the algorithm.