Informatica

An extended TODIM is proposed in this paper to comprehensively reflect the psychological characteristics of decision makers (DMs) according to cumulative prospect theory (CPT). We replace the original weight with the weighting function of CPT and modify the perceived value of the dominance based on CPT, because the general psychological phenomena of DMs explained in CPT are verified by many experiments and recognized by researchers. Hence, the extended TODIM not only integrates the advantages of CPT in considering the psychological factors of DMs but also retains the superiority of the classical TODIM in relative dominance. Finally, the extended TODIM is demonstrated to capture the psychological factors of DMs well from the case study.

The main contributions of this paper are shown as: (1) we define dual hesitant fuzzy t-norms and t-conorms; (2) based on dual hesitant fuzzy t-norms and t-conorms, we introduce a family of prioritized dual hesitant fuzzy operators to aggregate dual hesitant fuzzy information of alternatives with regard to the prioritized attributes; (3) we propose a method to handle the dual hesitant fuzzy multi-attribute decision making (MADM) problems with prioritized attributes; (4) we show that compared to other relevant studies, the developed prioritized aggregation operators take full advantage of the given decision information, avoid the loss of original information, and thus yield better final decision results.

This paper reviews the existing definitions and formulas of entropy for interval-valued intuitionistic fuzzy sets (IVIFSs) and demonstrates that they cannot fully capture the uncertainty of IVIFSs. Then considering both fuzziness and intuitionism of IVIFSs, we introduce a novel axiomatic definition of entropy for IVIFSs and develop several entropy formulas. Example analyses show that the developed entropy formulas can fully reflect both fuzziness and intuitionism of IVIFSs. Furthermore, based on the entropy formulas of IVIFSs, a method is proposed to solve multi-attribute decision making problems with IVIFSs. Additionally, an investment alternative selection example is provided to validate the practicality and effectiveness of the method.