Extension of TODIM method based on distance measures of decomposed fuzzy sets
Künye
Köseoğlu, A., Şahin, R. (2024). Extension of TODIM Method Based on Distance Measures of Decomposed Fuzzy Sets. In: Kahraman, C., Cevik Onar, S., Cebi, S., Oztaysi, B., Tolga, A.C., Ucal Sari, I. (eds) Intelligent and Fuzzy Systems. INFUS 2024. Lecture Notes in Networks and Systems, vol 1088. Springer, Cham. https://doi.org/10.1007/978-3-031-70018-7_78Özet
Fuzzy sets allow elements to have partial membership in a set, represented by a membership value between 0 and 1. This feature enables fuzzy sets to model imprecise or vague concepts. Decomposed fuzzy sets, an extension of fuzzy sets, have introduced a novel perspective in the literature by incorporating the Kano model into risk assessment. These sets have also paved the way for new approaches in decision-making methods, highlighting their functional and dysfunctional elements. In this paper, we propose a distance measure for decomposed fuzzy sets and subsequently extend the TODIM method based on this distance measure to DFSs. Then, we provide a numerical example to illustrate its effectiveness and practicality.
