A Group Decision Making Model for Integrating Heterogeneous Information

Abstract

This paper proposes a group decision-making (GDM) method for integrating heterogeneous information. To avoid information loss, instead of transforming heterogeneous information into a single form, the proposed method integrates heterogeneous information using a weighted-power average operator. The consensus degree between the individual-decision matrix and the group-decision matrix is then calculated based on the deviation degree. In addition, the feedback mechanism with the iterative algorithm is used to adjust the individual decision matrix, which does not reach the consensus. Furthermore, a ranking formula with heterogeneous technique for order preference by similarity to an ideal solution is adopted to select the best alternative. A numerical example of supplier selection is introduced to validate the proposed model and compare it with other similar GDM models. The results illustrate that the proposed method cannot only avoid information loss, but also effectively integrate heterogeneous information in heterogeneous GDM environment.