Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| CRITIC-M× | MEREC-G× | |
|---|---|---|
| Nozare | Lēmumu pieņemšana | Lēmumu pieņemšana |
| Saime | MCDM | MCDM |
| Izcelsmes gads≠ | 1995 | 2021 |
| Autors≠ | Based on Diakoulaki et al.'s CRITIC; modified variants developed later | Keshavarz Ghorabaee, Hosseinzadeh Lotfi et al. |
| Tips≠ | Objective weight derivation via correlation and variance | Objective weight derivation via removal impact assessment |
| Pirmavots≠ | Diakoulaki, D., Mavrotas, G., & Papayannakis, L. (1995). Determining objective weights in multiple criteria problems: The CRITIC method. Computers & Operations Research, 22(7), 763-770. DOI ↗ | Keshavarz Ghorabaee, M., Hosseinzadeh Lotfi, F., Behzadi, M., & Sałabun, W. (2021). MEREC: A new multi-criteria model to evaluate wind farm locations. Sustainability, 12(15), 6136. link ↗ |
| Citi nosaukumi | CRITIC-M, Modified CRITIC | MEREC-G, Generalized MEREC |
| Saistītās | 3 | 3 |
| Kopsavilkums≠ | CRITIC-M (Criteria Importance Through Intercriteria Correlation - Modified) is an objective weight derivation method that extends the classical CRITIC approach. It assigns weights to criteria based on two intrinsic properties of the decision matrix: variance (how much a criterion differentiates alternatives) and correlation (how much a criterion conflicts with or supplements others). Modified variants adjust the formulation to improve robustness or interpretability. | MEREC-G (Method Based on Removal Effects of Criteria - Generalized) is an objective weight derivation method that assigns weights based on the impact of removing each criterion from the decision analysis. The core idea is that important criteria, when removed, cause large changes in the final ranking. Generalized variants extend the original MEREC to various aggregation logic and decision contexts. |
| ScholarGateDatu kopa ↗ |
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