Abstract
To address the problem of multiattribute group decision-making with interval grey numbers, decision matrices are adjusted using kernels of interval grey numbers to reduce the psychological effects of decision-makers. The comprehensive weights of attributes are obtained by aggregating the subjective weights with objective weights, which are calculated based on the accuracy and difference of attributes. Considering the consistent, best, and worst decision-making abilities of decision-makers, grey incidence models are established to obtain the consistency weights and individual bipolar weights of decision-makers; then, the comprehensive weights of decision-makers are determined. A clustering approach of interval grey numbers is presented, and overall evaluations are obtained. Finally, an example is provided and its validity is tested to verify the feasibility of the proposed method.
Highlights
Multiattribute group decision-making (MAGDM) is a kind of decision-making method by which multiple experts rank, optimize, and classify a limited number of alternatives with multiple attributes according to certain criteria
MAGDM has been widely used in engineering [1], management [2], society [3, 4], and other fields [5]. e efficiency of the weights of decision-makers and attributes in MAGDM significantly affects the correctness of the results. erefore, a reliable methodology for determining the weights of decision-makers (DMs) and attributes is essential
For MAGDM with interval grey numbers, evaluation values are adjusted to reduce the psychological deviations of DMs
Summary
Multiattribute group decision-making (MAGDM) is a kind of decision-making method by which multiple experts rank, optimize, and classify a limited number of alternatives with multiple attributes according to certain criteria. Zhao et al [28] determined the weight of each DM by simultaneously considering similarity and proximity and developed a programming model with interval-valued intuitionistic fuzzy values based on crossentropy values to obtain attribute weights. Without comprehensively considering the kernel and its degree of greyness, conclusions are biased and cannot truly reflect the essential characteristics of interval grey numbers To address these problems, a new method of MAGDM was studied, in which interval grey numbers were treated as attribute values. E proposed methodology considered the DMs’ consistency and bipolar judgement on the best and worst alternatives and improved the weights of DMs. In the method, a new technique for weight determination of MAGDM with interval grey numbers is proposed.
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