A novel method for heterogeneous multi-attribute group decision making with preference deviation

Heterogeneous multi-attribute group decision making (HMAGDM) with preference deviation is a kind of complex and important problems in many decision situations. These problems involve real numbers, interval numbers, triangular fuzzy numbers, linguistic variables and intuitionistic fuzzy numbers. However, there are no general effective methods for solving such problems. The goal of this study is to develop a novel method for HMAGDM problems based on the onress measures by analyzing the relative closeness of alternatives and preference deviation degrees of each decision maker (DM). The weights of the attributes of each alternative and weights preference of DMs are obtained using two linear programming models. Furthermore, a ranking of alternatives is determined according to the decision making preference of alternatives. Finally, the validity and superiority of the proposed method are demonstrated using a real example and comparisons are conducted with the existing methods.