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Neural Computing and Applications

, Volume 30, Issue 1, pp 241–260 | Cite as

Multi-criteria group decision-making method based on interdependent inputs of single-valued trapezoidal neutrosophic information

  • Ru-xia Liang
  • Jian-qiang WangEmail author
  • Lin Li
Original Article

Abstract

Single-valued trapezoidal neutrosophic numbers (SVTNNs) are very useful tools for describing complex information, because they are able to maintain the completeness of the information and describe it accurately and comprehensively. This paper develops a method based on the single-valued trapezoidal neutrosophic normalized weighted Bonferroni mean (SVTNNWBM) operator to address multi-criteria group decision-making (MCGDM) problems. First, the limitations of existing operations for SVTNNs are discussed, after which improved operations are defined. Second, a new comparison method based on score function is proposed. Then, the entropy-weighted method is established in order to obtain objective expert weights, and the SVTNNWBM operator is proposed based on the new operations of SVTNNs. Furthermore, a single-valued trapezoidal neutrosophic MCGDM method is developed. Finally, a numerical example and comparison analysis are conducted to verify the practicality and effectiveness of the proposed approach.

Keywords

Multi-criteria group decision-making Single-valued trapezoidal neutrosophic number Single-valued trapezoidal neutrosophic weighted Bonferroni mean operator Entropy-weighted method 

Notes

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Nos. 71571193).

Compliance with ethical standards

Conflict of interest

The authors declare that there is no conflict of interest regarding the publication of this paper.

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Copyright information

© The Natural Computing Applications Forum 2016

Authors and Affiliations

  1. 1.School of BusinessCentral South UniversityChangshaPeople’s Republic of China
  2. 2.School of BusinessHunan UniversityChangshaPeople’s Republic of China

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