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Ranking of incomplete trapezoidal information

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Abstract

Any information system or decision model which consists of combinations of quantitative, qualitative, imprecise and incomplete informations can be modelled better using trapezoidal intuitionistic fuzzy numbers (TrIFNs) than interval valued intuitionistic fuzzy numbers. Ranking of TrIFNs plays an important role in intuitionistic fuzzy decision-making or intuitionistic fuzzy information system. In this paper, a new method for ranking of TrIFNs using membership, non-membership, vague and precise score functions which generalises the membership, non-membership, vague and precise score functions defined in Geetha et al. (Expert Syst Appl 41:1947–1954, 2014) is proposed and a new algorithm for solving information system problem with incomplete information is introduced. Further, the significance of our proposed method over the existing methods is studied by an illustrative example.

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Acknowledgments

The authors are grateful to the anonymous reviewers whose thoughtful remarks are greatly useful for the improvement of the paper.

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Authors and Affiliations

  1. Department of Mathematics, National Institute of Technology Tiruchirappalli, Tiruchirappalli, India

    V. Lakshmana Gomathi Nayagam & S. Jeevaraj

  2. Department of Mathematics, St. Joseph’s College (Autonomous), Tiruchirappalli, India

    Geetha Sivaraman

Authors
  1. V. Lakshmana Gomathi Nayagam
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  2. S. Jeevaraj
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  3. Geetha Sivaraman
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Corresponding author

Correspondence to S. Jeevaraj.

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The authors declare that they have no conflict of interest regarding the publication of this paper.

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This article does not contain any studies with human participants or animals performed by any of the authors.

Additional information

Communicated by V. Loia.

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Lakshmana Gomathi Nayagam, V., Jeevaraj, S. & Sivaraman, G. Ranking of incomplete trapezoidal information. Soft Comput 21, 7125–7140 (2017). https://doi.org/10.1007/s00500-016-2256-1

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  • DOI: https://doi.org/10.1007/s00500-016-2256-1

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