Induced 2-tuple linguistic generalized aggregation operators and their application in decision-making

The induced 2-tuple linguistic generalized ordered weighted averaging (2-TILGOWA) operator is presented. This new aggregation operator extends previous approaches by using generalized means, order-inducing variables in the reordering of the arguments and linguistic information represented with the 2-tuple linguistic approach. Its main advantage is that it includes a wide range of linguistic aggregation operators. Thus, its analyses can be seen from different perspectives and we obtain a much more complete picture of the situation considered and are able to select the alternative that best fits with our interests or beliefs. We further generalize the 2-TILGOWA by using quasi-arithmetic means and Choquet integrals. The result is the Quasi-2-TILOWA operator and the 2-tuple linguistic induced quasi-arithmetic Choquet integral aggregation. We conclude this paper by analysing the applicability of this new approach in a multi-person linguistic decision-making problem concerning product management.