विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| CRITIC-M× | MEREC-G× | |
|---|---|---|
| क्षेत्र | निर्णयन | निर्णयन |
| परिवार | MCDM | MCDM |
| उद्भव वर्ष≠ | 1995 | 2021 |
| प्रवर्तक≠ | Based on Diakoulaki et al.'s CRITIC; modified variants developed later | Keshavarz Ghorabaee, Hosseinzadeh Lotfi et al. |
| प्रकार≠ | Objective weight derivation via correlation and variance | Objective weight derivation via removal impact assessment |
| मौलिक स्रोत≠ | 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 ↗ |
| उपनाम | CRITIC-M, Modified CRITIC | MEREC-G, Generalized MEREC |
| संबंधित | 3 | 3 |
| सारांश≠ | 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. |
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