Majority Clusters-Density Ordered Weighting Averaging: A Family of New Aggregation Operators in Group Decision Making

In the process of aggregation, it is necessary, especially for group decision-making (GDM) problems, to consider distributed characteristic hidden in aggregates. In this case, clustering has been a common way for discovering the implicit distributed structures. This paper mainly investigates the characteristic of majority clusters, rather than majority elements and develops a new class of aggregation operators denominated majority clusters density-ordered weighting averaging (MC-DOWA) operators. Furthermore, we discuss properties of these operators and calculate the associated weights. Finally, a numerical example is provided to illustrate the application of the MC-DOWA operators, and the aggregations are compared with those of the other three aggregation operators: majority additive-OWA (MA-OWA), dependent OWA (DOWA) and cluster-based DOWA (Clus-DOWA) operators.