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A Correlation-Based TOPSIS Method for Multiple Attribute Decision Making with Single-Valued Neutrosophic Information

Author

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  • Shouzhen Zeng

    (School of Business, Ningbo University, Ningbo 315211, P. R. China)

  • Dandan Luo

    (School of Business, Ningbo University, Ningbo 315211, P. R. China)

  • Chonghui Zhang

    (#x2020;College of Statistics and Mathematics, Zhejiang Gongshang University, Hangzhou 310018, P. R. China)

  • Xingsen Li

    (#x2021;Research Institute of Extenics and Innovation Methods, Guangdong University of Technology, Guangzhou 510006, P. R. China)

Abstract

The single-valued neutrosophic set (SVNS) is considered as an attractive tool for handling highly uncertain and vague information. With this regard, different from the most current distance-based technique for order preference by similarity to ideal solution (TOPSIS) methods, this study proposes a correlation-based TOPSIS model for addressing the single-valued neutrosophic (SVN) multiple attribute decision making (MADM) problems. To achieve this aim, we first develop a novel conception of SVN correlation coefficient, whose significant feature is that it lies in the interval [−1,1], which is in accordance with the classical correlation coefficient in statistics, whereas all the existing SVN correlation coefficients in the literature are within unit interval [0,1]. Afterwards, a weighted SVN correlation coefficient is also introduced to infuse the importance of attributes. Moreover, a correlation-based comprehensive index is further proposed to establish the central structure of TOPSIS model, called the SVN correlation-based TOPSIS approach. Finally, a numerical example and relevant comparative analysis are implemented to explain the applicability and effectiveness of the mentioned methodology.

Suggested Citation

  • Shouzhen Zeng & Dandan Luo & Chonghui Zhang & Xingsen Li, 2020. "A Correlation-Based TOPSIS Method for Multiple Attribute Decision Making with Single-Valued Neutrosophic Information," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 19(01), pages 343-358, February.
    • Handle: RePEc:wsi:ijitdm:v:19:y:2020:i:01:n:s0219622019500512
    DOI: 10.1142/S0219622019500512
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    References listed on IDEAS

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    1. Peide Liu & Yumei Wang, 2019. "Intuitionistic Fuzzy Interaction Hamy Mean Operators and Their Application to Multi-attribute Group Decision Making," Group Decision and Negotiation, Springer, vol. 28(1), pages 197-232, February.
    2. Peide Liu & Junlin Liu & Shyi-Ming Chen, 2018. "Some intuitionistic fuzzy Dombi Bonferroni mean operators and their application to multi-attribute group decision making," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 69(1), pages 1-24, January.
    3. Shouzhen Zeng & Jianping Chen & Xingsen Li, 2016. "A Hybrid Method for Pythagorean Fuzzy Multiple-Criteria Decision Making," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 15(02), pages 403-422, March.
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    Cited by:

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    2. Baosheng Zhang & Tahir Mahmood & Jabbar Ahmmad & Qaisar Khan & Zeeshan Ali & Shouzhen Zeng, 2020. "Cubic q-Rung Orthopair Fuzzy Heronian Mean Operators and Their Applications to Multi-Attribute Group Decision Making," Mathematics, MDPI, vol. 8(7), pages 1-32, July.
    3. Shouzhen Zeng & Yingjie Hu & Tomas Balezentis & Dalia Streimikiene, 2020. "A multi‐criteria sustainable supplier selection framework based on neutrosophic fuzzy data and entropy weighting," Sustainable Development, John Wiley & Sons, Ltd., vol. 28(5), pages 1431-1440, September.
    4. Dandan Luo & Shouzhen Zeng & Ji Chen, 2020. "A Probabilistic Linguistic Multiple Attribute Decision Making Based on a New Correlation Coefficient Method and its Application in Hospital Assessment," Mathematics, MDPI, vol. 8(3), pages 1-16, March.

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