Uncertain Linguistic Multiple Attribute Group Decision Making Approach and Its Application to Software Project Selection

This paper proposes a new approach to solve the multiple attribute group decision making (MAGDM) problem where attribute values are in the format of uncertain linguistic information and attribute weights are in the format of linguistic information. Firstly, concepts and comparison laws of uncertain 2-tuple are given. Then, an uncertain 2-tuple ordered weighted averaging (UTOWA) operator is used to calculate alternative appraisal values with respect to all attributes for each decision maker (DM) and to aggregate all DMs’ preferences into a collective opinion. Furthermore, ranking alternatives or selecting the most desirable alternative(s) is conducted according to the comparison laws. Finally, a numerical example on software project selection is used to illustrate the applicability and effectiveness of the proposed approach.