Abstract
Rough neutrosophic set , a hybrid intelligent structure of rough set and neutrosophic set, is a powerful mathematical tool to deal with indeterminate, inconsistent and incomplete information, which has caught attention to the researchers. We present a brief review of decision making models in rough neutrosophic environment. In this chapter, we propose two aggregation operators, namely, a rough neutrosophic arithmetic mean operator (RNAMO) and a rough neutrosophic geometric mean operator (RNGMO). We establish some basic properties of the proposed operators. In the decision making situation, the rating of all alternatives is expressed with the upper and lower approximation operators and the pair of neutrosophic sets, which are characterized by truth-membership degree, indeterminacy-membership degree, and falsity membership degree. Weight of each criterion is completely unknown to the decision maker. We define a cosine function to obtain the unknown criteria weights in rough neutrosophic environment. We develop four new multi-criteria decision making methods based on the proposed operators. Finally, we solve a numerical example to illustrate the feasibility, applicability and efficiency of the proposed methods.
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Mondal, K., Pramanik, S., Giri, B.C. (2019). Rough Neutrosophic Aggregation Operators for Multi-criteria Decision-Making. In: Kahraman, C., Otay, İ. (eds) Fuzzy Multi-criteria Decision-Making Using Neutrosophic Sets. Studies in Fuzziness and Soft Computing, vol 369. Springer, Cham. https://doi.org/10.1007/978-3-030-00045-5_5
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