Selecting an aggregation operator for fuzzy decision making

In decision making one is interested in the preference ordering of the alternatives, rather than the exact numerical values that are assigned to the alternatives. This means that an aggregation operator that is able to combine criteria in a similar way to human beings need not reproduce the same numerical values as long as it produces a similar preference ordering as that of the humans. In this paper, previously published empirical data are analyzed from the point of view of preference orderings. A number of aggregation operators are used to approximate the preference ordering done by human beings. None of the operators give very good results. Moreover, there is not a significant difference in the performance of the t-norms or the compensatory operators. The operators can achieve, however, a partially correct ordering of the alternatives.<>