Abstract:The proposed work introduces a new methodology for solving Multiple Attribute Decision Making (MADM) problems in which the alternatives are assessed as hesitant fuzzy linguistic value (HFLV) over the attributes. The proposed MADM problem is exhibited as a rough set model with set-valued data as HFLVs. A similarity measure is defined in the set-valued information system that aids to remove the irrelevant or redundant attributes. The uncertainty due to hesitancy in HFLVs and the linked anxiety of the decision-ma… Show more
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