Novel approach to multi-attribute group decision-making based on interval-valued Pythagorean fuzzy power Maclaurin symmetric mean operator
•For comparing any two interval-valued Pythagorean fuzzy numbers, a novel comparison method is introduced.•We introduce PA and MCM operators into IVPFS, and propose some new operators for IVPFS.•With the aid of the WIVPFPMSM operator, we design the new extension approach for MAGDM. To distinguish an...
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| Vydané v: | Computers & industrial engineering Ročník 155; s. 107049 |
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| Hlavní autori: | , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
Elsevier Ltd
01.05.2021
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| Predmet: | |
| ISSN: | 0360-8352 |
| On-line prístup: | Získať plný text |
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| Shrnutí: | •For comparing any two interval-valued Pythagorean fuzzy numbers, a novel comparison method is introduced.•We introduce PA and MCM operators into IVPFS, and propose some new operators for IVPFS.•With the aid of the WIVPFPMSM operator, we design the new extension approach for MAGDM.
To distinguish any two interval-valued Pythagorean fuzzy numbers (IVPFNs), two new comparison functions, namely, the membership degree uncertainty (MU) function and the hesitation degree uncertainty (HU) function are proposed in this paper. By combining the existing score and accuracy functions with the proposed MU and HU functions, a new comparison rule for IVPFNs is obtained, whereby two different IVPFNs may be distinguished. Then, the interval-valued intuitionistic Pythagorean fuzzy power Maclaurin symmetric mean aggregation (IVPFPMSM) operator and the weighted IVIPFMSM aggregation operator are introduced to address complex multi-attribute group decision-making (MAGDM) problems involving unreasonable evaluation values and interaction among the input arguments. Moreover, a series of properties of the proposed operators are studied. Further, based on the proposed comparison method for IVPFNs and the weighted IVPFPMSM operator, we develop a new method for interval-valued Pythagorean fuzzy MAGDM problems. Finally, two illustrative examples and a comparative analysis are provided to demonstrate the effectiveness and superiority of the proposed method. Specifically, the advantage of the proposed operators in MAGDM problems is that they can eliminate bad influences of extreme evaluation values from biased decision makers and capture the interaction between attributes. |
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| ISSN: | 0360-8352 |
| DOI: | 10.1016/j.cie.2020.107049 |