Integrating TOPSIS with interval-valued intuitionistic fuzzy cognitive maps for effective group decision making.

Many real-life situations require ranking alternative decisions with respect to multiple criteria. The problem becomes more complicated when the knowledge of the considered criteria is vague and unreliable. In order to cope with the vagueness, the values of criteria have to be represented in an approximated way. To overcome the lack of reliability, many experts can be involved in the decision process and thus cooperatively elaborate more credible decisions. However, as it turns out, experts are usually unable to provide plausible information on interactions between vague decision criteria. Since those interactions substantially affect the ranking of alternative decisions, they should be taken into account in the decision process. To effectively cope with that issue, we propose a novel multi-criteria group decision-making method that integrates TOPSIS (technique for order of preference by similarity to ideal solution) with IVIFCMs (interval-valued intuitionistic fuzzy cognitive maps), a tool that is able to model interactions among highly imprecise criteria. We illustrate the application of the proposed IVIFCM-TOPSIS to the supplier selection task. Finally, we present the advantages derived from the use of our method compared to competitive approaches known from the literature. In particular, we show that our method is more consistent than the existing state-of-the-art methods used to solve the addressed decision problem.