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Вероятностно-колебателно разширение на COPRAS×Метод "Най-добър-Най-лош"×Значимост на критериите чрез междукритерийна корелация×
ОбластВземане на решенияВземане на решенияВземане на решения
СемействоMCDMMCDMMCDM
Година на възникване202120151995
СъздателSong, H. F. Chen, Z. C.Rezaei, J.Diakoulaki, D., Mavrotas, G., Papayannakis, L.
ТипProbabilistic Hesitant ranking — Probabilistic Hesitant Fuzzy Element (PHFE: {γ|p} pairs)Pairwise comparison (best-to-others + others-to-worst vectors), LPStatistical contrast intensity + correlation-based objective weighting
Основополагащ източникSong, H. F., Chen, Z. C. (2021). Multi-attribute decision-making method based distance and COPRAS method with probabilistic hesitant fuzzy environment. International Journal of Computational Intelligence Systems DOI ↗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 DOI ↗
Други названия
Свързани888
РезюмеPHF-COPRAS (Probabilistic Hesitant extension of COPRAS) is a ranking multi-criteria decision-making (MCDM) method introduced by Song, H. F. Chen, Z. C. in 2021. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.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 (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.
ScholarGateНабор от данни
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ScholarGateСравнение на методи: PHF-COPRAS · BWM · CRITIC. Извлечено на 2026-06-19 от https://scholargate.app/bg/compare