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.