Heavy weighted geometric aggregation operators in analytic hierarchy process-group decision making

In this paper, some heavy weighted geometric aggregation operators in analytic hierarchy process under group decision making (AHP-GDM) are proposed. First, in the sense of heavy ordered weighted averaging operator, the heavy weighted geometric (HWG) and heavy ordered weighted geometric (HOWG) operators are introduced as extensions of the normal weighted geometric mean and the ordered weighted geometric by relaxing the constraints on the associated weighting vector. These HWG and HOWG then are utilized in the aggregation process of AHP-GDM as to maintain the multiplicative reciprocal property, specifically on the aggregation of individual judgments procedure. The main advantage of the model, besides the complete overlapping of information such in classical methods, is that it can also accommodate partial and non-overlapping information in the formulation. To show the applicability of the proposed method, a numerical example in an investment selection problem is provided.