Group decision making based on computing with linguistic variables and an example in information system selection

In decision making problems with multiple experts as group decision making (GDM), each expert expresses his/her preferences or judgments depending on his/her own knowledge or experiences. A more realistic approach may be to use linguistic assessments instead of numerical values. Therefore, decision-makerspsila opinions are described by linguistic variables which can be expressed in different types. In this paper, a transformation method will be presented to transform the non-homogeneous linguistic information to a standard linguistic term set. Then, a decision-making model is proposed based on computing with 2-tuple linguistic variables to deal with the group decision making problems. According to the concept of the TOPSIS, a 2-tuple linguistic closeness coefficient is defined to determine the ranking order of all alternatives by calculating the distances to the both linguistic positive-ideal solution (LPIS) and linguistic negative-ideal solution (LNIS) simultaneously. Finally, an example of information system selection is implemented at the end of this paper to demonstrate the procedure for the proposed method.