Open Access
ARTICLE
Abstract
Due to the complexity of decision-making problems and the subjectivity of decision-makers in practical application, it is necessary to adopt different forms of information expression according to the actual situation of specific decision-making problems and choose the best method to solve them. Multi-valued neutrosophic set, as an extension of neutrosophic set, can more effectively and accurately describe incomplete, uncertain or inconsistent information. TODIM and TOPSIS methods are two commonly used multi-attribute decision-making methods, each of which has its advantages and disadvantages. This paper proposes a new method based on TODIM and TOPSIS to solve multi-attribute decision-making problems under multi-valued neutrosophic environment. After introducing the related theory of multi-valued neutrosophic set and the traditional TODIM and TOPSIS methods, the new method based on a combination of TODIM and TOPSIS methods is described. And then, two illustrative examples proved the feasibility and validity of the proposed method. Finally, the result has been compared with some existing methods under the same examples and the proposed method's superiority has been proved. This paper studies this kind of decision-making problem from algorithm idea, algorithm steps and decision-making influencing factors.
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Cite This Article
APA Style
Xu, D., Peng, L. (2021). An improved method based on TODIM and TOPSIS for multi-attribute decision-making with multi-valued neutrosophic sets. Computer Modeling in Engineering & Sciences, 129(2), 907-926. https://doi.org/10.32604/cmes.2021.016720
Vancouver Style
Xu D, Peng L. An improved method based on TODIM and TOPSIS for multi-attribute decision-making with multi-valued neutrosophic sets. Comput Model Eng Sci. 2021;129(2):907-926 https://doi.org/10.32604/cmes.2021.016720
IEEE Style
D. Xu and L. Peng, "An Improved Method Based on TODIM and TOPSIS for Multi-Attribute Decision-Making with Multi-Valued Neutrosophic Sets," Comput. Model. Eng. Sci., vol. 129, no. 2, pp. 907-926. 2021. https://doi.org/10.32604/cmes.2021.016720