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Erschienen in: Knowledge and Information Systems 11/2020

07.08.2020 | Regular Paper

Pythagorean fuzzy MULTIMOORA method based on distance measure and score function: its application in multicriteria decision making process

verfasst von: Chao Huang, Mingwei Lin, Zeshui Xu

Erschienen in: Knowledge and Information Systems | Ausgabe 11/2020

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Abstract

The MULTIMOORA method is better than some of the existing decision making methods. However, it has not been improved to process Pythagorean fuzzy sets (PFSs). The decision results of the MULTIMOORA method greatly depend on the distance measure and score function. Although there are many studies focusing on proposing distance measures and score functions for PFSs, they still show some defects. In this paper, we propose two novel distance measures and a novel score function for PFSs for proposing a novel Pythagorean fuzzy MULTIMOORA method. To this end, two distance measures, Dice distance and Jaccard distance, are proposed for computing the deviation degree between two PFSs, and their general forms are also discussed. Afterward, a novel score function based on determinacy degree and indeterminacy degree is put forward for approximately representing PFSs. Then, the original MULTIMOORA method is extended by using the Dice distance and score function and it is used to solve the multicriteria decision making problems under the PFS information context. Finally, a real case for evaluating solid-state disk productions is handled using the proposed Pythagorean fuzzy MULTIMOORA method and another case for evaluating energy projects is given to verify the advantages of our studies by comparing them with the existing Pythagorean fuzzy distance measures, score functions, and decision making methods.

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Metadaten
Titel
Pythagorean fuzzy MULTIMOORA method based on distance measure and score function: its application in multicriteria decision making process
verfasst von
Chao Huang
Mingwei Lin
Zeshui Xu
Publikationsdatum
07.08.2020
Verlag
Springer London
Erschienen in
Knowledge and Information Systems / Ausgabe 11/2020
Print ISSN: 0219-1377
Elektronische ISSN: 0219-3116
DOI
https://doi.org/10.1007/s10115-020-01491-y

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