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Entropy on interval-valued intuitionistic fuzzy sets and its application in multi-attribute decision making

  • School of Computer Science and Technology, Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This article proposes a new axiomatic definition of entropy on interval-valued intuitionistic fuzzy sets (IVIFSs) and a method to construct different entropies on IVIFSs. Furthermore, a new multi-attribute decision making (MADM) method based on similarity measures using entropy-based attribute weights is proposed to deal with the decision making situations where the alternatives on attributes are expressed by IVIFSs and the attribute weights information is unknown. Instead of using traditional fuzzy entropy, which obtain attribute weights through the probabilistic discrimination of attributes, we utilize the interval-valued intuitionistic fuzzy (IVIF) entropy to assess attribute weights based on the credibility of the IVIF decision making matrix. Finally, two numerical examples are given to demonstrate the feasibility and validity of the newly proposed MADM method, by comparing it with other fuzzy MADM methods.

Original languageEnglish
Title of host publicationFusion 2011 - 14th International Conference on Information Fusion
StatePublished - 2011
Event14th International Conference on Information Fusion, Fusion 2011 - Chicago, IL, United States
Duration: 5 Jul 20118 Jul 2011

Publication series

NameFusion 2011 - 14th International Conference on Information Fusion

Conference

Conference14th International Conference on Information Fusion, Fusion 2011
Country/TerritoryUnited States
CityChicago, IL
Period5/07/118/07/11

Keywords

  • Entropy
  • Interval-valued intuitionistic fuzzy sets (IV-IFSs)
  • Multi-attribute decision making (MADM)

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