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चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।

SPOTIS का न्यूट्रोसोफिक विस्तार×सर्वश्रेष्ठ-निकृष्टतम विधि (Best-Worst Method)×बायेसियन BWM×
क्षेत्रनिर्णयननिर्णयननिर्णयन
परिवारMCDMMCDMMCDM
उद्भव वर्ष202320152020
प्रवर्तकAbdel-aziem, A. H., Mohamed, H. K., Abdelhafeez, A.Rezaei, J.Mohammadi, M., Rezaei, J.
प्रकारNeutrosophic outranking/ranking — Single-Valued Neutrosophic Set (SVNS: T, I, F; T,I,F ∈ [0,1], T+I+F ≤ 3)Pairwise comparison (best-to-others + others-to-worst vectors), LPHierarchical Dirichlet posterior over weights via MCMC (JAGS) — group decision
मौलिक स्रोतAbdel-aziem, A. H., Mohamed, H. K., Abdelhafeez, A. (2023). Neutrosophic Decision Making Model for Investment Portfolios Selection and Optimizing based on Wide Variety of Investment Opportunities and Many Criteria in Market. Neutrosophic Systems with Applications DOI ↗Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega DOI ↗Mohammadi, M., Rezaei, J. (2020). Bayesian best-worst method: A probabilistic group decision making model. Omega DOI ↗
उपनाम
संबंधित888
सारांशN-SPOTIS (Neutrosophic extension of SPOTIS) is a ranking multi-criteria decision-making (MCDM) method introduced by Abdel-aziem, A. H., Mohamed, H. K., Abdelhafeez, A. in 2023. 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.BWM-BAYESIAN (Bayesian BWM — Probabilistic Group Best-Worst Method) is a weight subjective multi-criteria decision-making (MCDM) method introduced by Mohammadi, M., Rezaei, J. in 2020. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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ScholarGateविधियों की तुलना करें: N-SPOTIS · BWM · BWM-BAYESIAN. 2026-06-19 को यहाँ से प्राप्त https://scholargate.app/hi/compare