2020
DOI: 10.3390/axioms9030104
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An Extended MABAC Method Based on Triangular Fuzzy Neutrosophic Numbers for Multiple-Criteria Group Decision Making Problems

Abstract: In this manuscript, we extend the traditional multi-attributive border approximation area comparison (MABAC) method for the multiple-criteria group decision-making (MCGDM) with triangular fuzzy neutrosophic numbers (TFNNs) to propose the TFNNs-MABAC method. In the proposed method, we utilize the TFNNs to express the values of criteria for each alternative in MCGDM problems. First, we briefly acquaint the basic concept of TFNNs and describe its corresponding some operation laws, the functions of score and accur… Show more

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Cited by 34 publications
(4 citation statements)
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“…Then, the TFN-TODIM-TOPSIS method is compared with TFNNWA operator and TFNNWG operator [64], TFN-VIKOR [72], TFN-MABAC [65] and TFN-EDAS [73]. The comparative decision results are shown in Table 6.…”
Section: B Comparative Analysismentioning
confidence: 99%
“…Then, the TFN-TODIM-TOPSIS method is compared with TFNNWA operator and TFNNWG operator [64], TFN-VIKOR [72], TFN-MABAC [65] and TFN-EDAS [73]. The comparative decision results are shown in Table 6.…”
Section: B Comparative Analysismentioning
confidence: 99%
“…Applied Computational Intelligence and Soft Computing realistic weight matrix and more rational decision results. Additionally, it is also important to develop the EDAS method based on some other neutrosophic sets and fuzzy sets, such as bipolar trapezoidal neutrosophic sets [41], complex intuitionistic uncertain linguistic Heronian mean [42], and triangular fuzzy neutrosophic set [43].…”
Section: Conclusion and Future Studiesmentioning
confidence: 99%
“…In this situation, GDM that allows large-scale decision-makers to participate in the decision-making process has received increasing attention and has been widely applied [49][50][51][52][53]. Compared with decision-making, group decision-making can fully utilize various resources, fully leverage the advantages of different knowledge structures, and improve the comprehensiveness and objectivity of the decision-making process and results [54][55][56][57][58][59]. The quality evaluation of large-scale multi-view 3D reconstruction is MAGDM.…”
Section: Introductionmentioning
confidence: 99%