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이중 망설임 퍼지 COPRAS 확장×Criteria Correlation and Standard Deviation (CCSD) 가중치 결정 방법×
분야의사결정의사결정
계열MCDMMCDM
기원 연도20202010
창시자Rani, P., Mishra, A. R., Krishankumar, R., Mardani, A., Cavallaro, F., Ravichandran, K. S., Balasubramanian, K.Wang, Y. M., Luo, Y.
유형Dual Hesitant outranking/ranking — Dual Hesitant Fuzzy Element (DHFE: h(x) membership set, g(x) non-membership set)Correlation-penalised standard-deviation weighting
원전Rani, P., Mishra, A. R., Krishankumar, R., Mardani, A., Cavallaro, F., Ravichandran, K. S., Balasubramanian, K. (2020). Hesitant Fuzzy SWARA-Complex Proportional Assessment Approach for Sustainable Supplier Selection (HF-SWARA-COPRAS). Symmetry DOI ↗Wang, Y. M., Luo, Y. (2010). Integration of correlations with standard deviations for determining attribute weights in multiple attribute decision making. Mathematical and Computer Modelling DOI ↗
별칭
관련88
요약DHF-COPRAS (Dual Hesitant Fuzzy extension of COPRAS) is a ranking multi-criteria decision-making (MCDM) method introduced by Rani, P., Mishra, A. R., Krishankumar, R., Mardani, A., Cavallaro, F., Ravichandran, K. S., Balasubramanian, K. in 2020. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.CCSD (Criteria Correlation and Standard Deviation objective weighting) is a weight objective multi-criteria decision-making (MCDM) method introduced by Wang, Y. M., Luo, Y. in 2010. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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