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Wuhan University Journal of Natural Sciences
Article . 2015 . Peer-reviewed
License: Springer TDM
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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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https://dx.doi.org/10.1007/s11...
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An interactive intuitionistic fuzzy method for multilevel linear programming problems

descriptionPublicationkeyboard_double_arrow_right Article 01 Apr 2015 English Publisher:EDP SciencesJournal:Wuhan University Journal of Natural Sciences, volume 20, pages 113-118 (issn: 1007-1202, eissn: 1993-4998, Copyright policy )
Authors: Huang, Chan; Fang, Debin; Wan, Zhongping;

doi: 10.1007/s11859-015-1068-y

An interactive intuitionistic fuzzy method for multilevel linear programming problems

Abstract

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Keywords

intuitionistic fuzzy method, multilevel linear programming, Linear programming, Fuzzy and other nonstochastic uncertainty mathematical programming, satisfying degree

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Top 10%
Average
Average
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