A Correlation-Based TOPSIS Method for Multiple Attribute Decision Making with Single-Valued Neutrosophic Information
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DOI: 10.1142/S0219622019500512
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- 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.
- 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.
- 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:
- Lihua Liu & Jing Huang & Huimin Wang, 2020. "Visibility Graph Power Geometric Aggregation Operator and Its Application in Water, Energy and Food Efficiency Evaluation," IJERPH, MDPI, vol. 17(11), pages 1-16, May.
- 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.
- 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.
- 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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Keywords
Single-valued neutrosophic set; TOPSIS; correlation coefficient; MADM;All these keywords.
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