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A group decision making approach in interval-valued intuitionistic hesitant fuzzy environment with confidence levels

The main purpose of this paper is to research the multi-attribute group decision making (MAGDM) problems with interval-valued hesitant fuzzy numbers based on the confidence level. In this paper, we provide the confidence level of decision-making information which is applicable to put forward an optimized weight solution. Then we define the interval- valued intuitionistic hesitant fuzzy operator to aggregate decision information combing the ϕs transformation and Choquet integral. Taking the disadvantage of ranking by distance into account, we propose a ranking approach using the interval-valued intuitionistic hesitant fuzzy entropy. Finally, an illustrative example has been made to demonstrate the validity and feasibility of the proposed method.