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Surapati Pramanik
Researcher at Indian Institute of Engineering Science and Technology, Shibpur
Publications - 176
Citations - 4890
Surapati Pramanik is an academic researcher from Indian Institute of Engineering Science and Technology, Shibpur. The author has contributed to research in topics: Interval (mathematics) & Similarity measure. The author has an hindex of 34, co-authored 173 publications receiving 4515 citations. Previous affiliations of Surapati Pramanik include Indian Institute of Technology Kharagpur.
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Topsis Method for Multi-Attribute Group Decision Making Under Single-Valued Neutrosophic Environment
TL;DR: A new approach for multi-attribute group decision-making problems is proposed by extending the technique for order preference by similarity to ideal solution to single-valued neutrosophic environment.
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TOPSIS method for multi-attribute group decision-making under single-valued neutrosophic environment
TL;DR: In this article, a new approach for multi-attribute group decision-making problems is proposed by extending the technique for order preference by similarity to ideal solution to single-valued neutrosophic environment.
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Fuzzy goal programming approach to multilevel programming problems
TL;DR: A procedure for solving multilevel programming problems in a large hierarchical decentralized organization through linear fuzzy goal programming approach, which achieves highest degree of each of the membership goals by minimizing negative deviational variables.
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Entropy Based Grey Relational Analysis Method for Multi- Attribute Decision Making under Single Valued Neutrosophic Assessments
TL;DR: In this paper, the grey relational analysis method is applied to multi-attribute decision making problem with single-valued neutrosophic attribute values, where the rating of all alternatives is expressed with a singlevalued set, which is characterised by truth-membership degree, indeterminacy-memberships degree, and falsity-Membership degree.
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A New Methodology for Neutrosophic Multi-attribute Decision-making with Unknown Weight Information
TL;DR: The modified grey relational analysis method is proposed to find out the best alternative for multi-attribute decision- making problem under neutrosophic environment and establishes a deviation based optimization model based on the ideal alternative to determine attribute weight in which the information about attribute weights is incompletely known.