Type-2 OWA operators - aggregating type-2 fuzzy sets in soft decision making

Yagerpsilas ordered weighted averaging (OWA) operator has been widely used in soft decision making to aggregate expertspsila individual opinions or preferences for achieving an overall decision. The traditional Yagerpsilas OWA operator focuses exclusively on the aggregation of crisp numbers. However, human experts usually tend to express their opinions or preferences in a very natural way via linguistic terms, like ldquoimportantrdquo , ldquovery importantrdquo, ldquogoodrdquo etc.. Type-2 fuzzy sets provide an efficient way of knowledge representation for modelling linguistic terms. In order to aggregate linguistic opinions via the OWA mechanism, we propose a new type of OWA operator, termed type-2 OWA operator that is able to aggregate type-2 fuzzy sets, and therefore to aggregate the linguistic opinions or preferences in human decision making. The necessary equations for performing type-2 OWA operations on aggregating interval type-2 fuzzy sets are derived in this paper. Some examples are provided to illustrate the proposed technique.