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。

MULTIMOORA的概率语言扩展×基于标准移除效应的方法×
领域决策决策
方法族MCDMMCDM
起源年份20182021
提出者Wu, X. Liao, H. Xu, Z. S. Hafezalkotob, A. Herrera, F.Keshavarz Ghorabaee, M., Amiri, M., Zavadskas, E. K., Antucheviciene, J., Turskis, Z.
类型Probabilistic Linguistic multi-objective ranking — PLTS: {L_k|p_k} with expectation function + Borda aggregationRemoval-effect objective weighting (logarithmic utility)
开创性文献Wu, X., Liao, H., Xu, Z. S., Hafezalkotob, A., Herrera, F. (2018). Probabilistic Linguistic MULTIMOORA: A Multicriteria Decision Making Method Based on the Probabilistic Linguistic Expectation Function and the Improved Borda Rule. IEEE Transactions on Fuzzy Systems DOI ↗Keshavarz Ghorabaee, M., Amiri, M., Zavadskas, E. K., Antucheviciene, J., Turskis, Z. (2021). Determination of objective weights using a new method based on the removal effects of criteria (MEREC). Informatica DOI ↗
别名
相关88
摘要PL-MULTIMOORA (Probabilistic Linguistic extension of MULTIMOORA) is a ranking multi-criteria decision-making (MCDM) method introduced by Wu, X. Liao, H. Xu, Z. S. Hafezalkotob, A. Herrera, F. in 2018. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.MEREC (MEthod based on the Removal Effects of Criteria) is a weight objective multi-criteria decision-making (MCDM) method introduced by Keshavarz Ghorabaee, M., Amiri, M., Zavadskas, E. K., Antucheviciene, J., Turskis, Z. in 2021. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
ScholarGate数据集
  1. v1
  2. 1 来源
  3. PUBLISHED
  1. v1
  2. 1 来源
  3. PUBLISHED

前往搜索 下载幻灯片

ScholarGate方法对比: PL-MULTIMOORA · MEREC. 于 2026-06-17 检索自 https://scholargate.app/zh/compare