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Granular Computing
Erschienen in: Granular Computing 3/2023

06.08.2022 | Original Paper

Multi-attribute decision-making based on the advanced possibility degree measure of intuitionistic fuzzy numbers

verfasst von: Chirag Dhankhar, Kamal Kumar

Erschienen in: Granular Computing | Ausgabe 3/2023

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Abstract

In this paper, we propose a novel multi-attribute decision-making (MADM) approach for the intuitionistic fuzzy numbers (IFNs) environment. For this, we propose the advanced possibility degree measure (APDM) to rank the intuitionistic fuzzy numbers (IFNs). We also explore the properties of the proposed APDM of IFNs. The proposed APDM of IFNs can overcome the drawbacks of the existing possibility degree measure (PDM) of IFNs. Moreover, we propose a novel multi-attribute decision-making approach based on the proposed APDM of IFNs environment. We also explore the drawbacks of the existing MADM approach in the environment of IFNs, which has the drawback that it cannot distinguish the ranking order (RO) of the alternatives in some circumstances. The proposed MADM approach can overcome the drawbacks of the existing MADM approach. The proposed MADM approach offers us a very useful way to deal with MADM problems in the context of IFNs.
Vorheriger Artikel Extended CODAS method for multi-attribute group decision-making based on 2-tuple linguistic Fermatean fuzzy Hamacher aggregation operators
Nächster Artikel A solution algorithm for finding the best and the worst fuzzy compromise solutions of fuzzy rough linear programming problem with triangular fuzzy rough number coefficients

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Metadaten
Titel
Multi-attribute decision-making based on the advanced possibility degree measure of intuitionistic fuzzy numbers
verfasst von
Chirag Dhankhar
Kamal Kumar
Publikationsdatum
06.08.2022
Verlag
Springer International Publishing
Erschienen in
Granular Computing / Ausgabe 3/2023
Print ISSN: 2364-4966
Elektronische ISSN: 2364-4974
DOI
https://doi.org/10.1007/s41066-022-00343-0

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