Normal neutrosophic multiple attribute decision making based on generalized prioritized aggregation operators
Normal neutrosophic set, which allows a combination of the normal fuzzy number and the neutrosophic number, is a powerful tool for handling the incompleteness, indeterminacy and inconsistency of evaluation information. Based on the opinion of prioritized aggregation operators developed to describe the prioritization relationships among several attributes, this paper investigates some prioritized aggregation operators for aggregating the normal neutrosophic information, such as normal neutrosophic prioritized weighted averaging operator and normal neutrosophic prioritized weighted geometric operator, and then extends these operators to the generalized prioritized weighted aggregation operators, including normal neutrosophic generalized prioritized weighted averaging operator and normal neutrosophic generalized prioritized weighted geometric operator, respectively. They can take into account the prioritization facts in the aggregated information. Moreover, some of their desirable properties are investigated in detail. A multiple attribute decision-making method is developed for solving a kind of problems in which the decision attributes have different priority level commonly and they take the form of normal neutrosophic numbers. Finally, an illustrative example based on the prioritization relationship over the evaluation data is given to depict the effectiveness and feasibility of the developed decision-making method, which are then compared to the existing approaches. © 2017, The Natural Computing Applications Forum.
SourceNeural Computing and Applications
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