পদ্ধতির তুলনা করুন

	SNHF-TOPSIS	TOPSIS-এর নিউট্রো সফিক এক্সটেনশন
ক্ষেত্র	সিদ্ধান্ত গ্রহণ	সিদ্ধান্ত গ্রহণ
পরিবার	MCDM	MCDM
উদ্ভবের বছর	2019	2016
প্রবর্তক	Akram, M. Naz, S. Smarandache, F.	Biswas, P., Pramanik, S., Giri, B. C.
ধরন	Simplified Neutrosophic Hesitant Fuzzy TOPSIS — decision matrix entries are SVNHFEs (each of T, I, F is a finite set of values in [0,1]); weights derived internally via Maximizing Deviation Method	Neutrosophic outranking/ranking — Single-Valued Neutrosophic Set (SVNS: T, I, F; T,I,F ∈ [0,1], T+I+F ≤ 3)
মৌলিক উৎস	Akram, M., Naz, S., Smarandache, F. (2019). Generalization of Maximizing Deviation and TOPSIS Method for MADM in Simplified Neutrosophic Hesitant Fuzzy Environment. Symmetry	Biswas, P., Pramanik, S., Giri, B. C. (2016). TOPSIS method for multi-attribute group decision-making under single-valued neutrosophic environment. Neural Computing and Applications
অপর নাম	—	—
সম্পর্কিত	2	8
সারসংক্ষেপ	SNHF-TOPSIS (TOPSIS with Maximizing Deviation in Simplified Neutrosophic Hesitant Fuzzy Environment) is a ranking multi-criteria decision-making (MCDM) method introduced by Akram, M. Naz, S. Smarandache, F. in 2019. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.	N-TOPSIS (Neutrosophic extension of TOPSIS) is a ranking multi-criteria decision-making (MCDM) method introduced by Biswas, P., Pramanik, S., Giri, B. C. in 2016. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.