Salīdzināt metodes
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| SNHF-TOPSIS× | Neitrosofiskā TOPSIS paplašinājums× | |
|---|---|---|
| Nozare | Lēmumu pieņemšana | Lēmumu pieņemšana |
| Saime | MCDM | MCDM |
| Izcelsmes gads≠ | 2019 | 2016 |
| Autors≠ | Akram, M. Naz, S. Smarandache, F. | Biswas, P., Pramanik, S., Giri, B. C. |
| Tips≠ | Simplified Neutrosophic Hesitant Fuzzy TOPSIS — decision matrix entries are SVNHFEs (each of T, I, F is a finite set of values in [0,1]); weights derived internally via Maximizing Deviation Method | Neutrosophic outranking/ranking — Single-Valued Neutrosophic Set (SVNS: T, I, F; T,I,F ∈ [0,1], T+I+F ≤ 3) |
| Pirmavots≠ | Akram, M., Naz, S., Smarandache, F. (2019). Generalization of Maximizing Deviation and TOPSIS Method for MADM in Simplified Neutrosophic Hesitant Fuzzy Environment. Symmetry DOI ↗ | Biswas, P., Pramanik, S., Giri, B. C. (2016). TOPSIS method for multi-attribute group decision-making under single-valued neutrosophic environment. Neural Computing and Applications DOI ↗ |
| Citi nosaukumi | — | — |
| Saistītās≠ | 2 | 8 |
| Kopsavilkums≠ | SNHF-TOPSIS (TOPSIS with Maximizing Deviation in Simplified Neutrosophic Hesitant Fuzzy Environment) is a ranking multi-criteria decision-making (MCDM) method introduced by Akram, M. Naz, S. Smarandache, F. in 2019. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. | N-TOPSIS (Neutrosophic extension of TOPSIS) is a ranking multi-criteria decision-making (MCDM) method introduced by Biswas, P., Pramanik, S., Giri, B. C. in 2016. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. |
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