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| CRiteria Importance Through Intercriteria Correlation× | MEREC-G× | |
|---|---|---|
| Bidang | Pembuatan Keputusan | Pembuatan Keputusan |
| Keluarga | MCDM | MCDM |
| Tahun asal≠ | 1995 | 2021 |
| Pengasas≠ | Diakoulaki, D., Mavrotas, G., Papayannakis, L. | Keshavarz Ghorabaee, Hosseinzadeh Lotfi et al. |
| Jenis≠ | Statistical contrast intensity + correlation-based objective weighting | Objective weight derivation via removal impact assessment |
| Sumber perintis≠ | Diakoulaki, D., Mavrotas, G., Papayannakis, L. (1995). Determining objective weights in multiple criteria problems: The CRITIC method. Computers & Operations Research 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 ↗ |
| Alias≠ | — | MEREC-G, Generalized MEREC |
| Berkaitan≠ | 8 | 3 |
| Ringkasan≠ | CRITIC (CRiteria Importance Through Intercriteria Correlation) is a weight objective multi-criteria decision-making (MCDM) method introduced by Diakoulaki, D., Mavrotas, G., Papayannakis, L. in 1995. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. | 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. |
| ScholarGateSet data ↗ |
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