ScholarGate
助手

方法对比

并排查看您选择的方法;存在差异的行会高亮显示。

最佳-最差法 (Best-Worst Method)×CRITIC-M×MEREC-G×
领域决策决策决策
方法族MCDMMCDMMCDM
起源年份201519952021
提出者Rezaei, J.Based on Diakoulaki et al.'s CRITIC; modified variants developed laterKeshavarz Ghorabaee, Hosseinzadeh Lotfi et al.
类型Pairwise comparison (best-to-others + others-to-worst vectors), LPObjective weight derivation via correlation and varianceObjective weight derivation via removal impact assessment
开创性文献Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega DOI ↗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 ↗
别名CRITIC-M, Modified CRITICMEREC-G, Generalized MEREC
相关833
摘要BWM (Best-Worst Method) is a weight subjective multi-criteria decision-making (MCDM) method introduced by Rezaei, J. in 2015. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.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.
ScholarGate数据集
  1. v1
  2. 1 来源
  3. PUBLISHED
  1. v1
  2. 2 来源
  3. PUBLISHED
  1. v1
  2. 2 来源
  3. PUBLISHED

前往搜索 下载幻灯片

ScholarGate方法对比: BWM · CRITIC-M · MEREC-G. 于 2026-06-20 检索自 https://scholargate.app/zh/compare