A Multi-attribute Large Group Decision-making Method Based on Public Dual Valuation with Unknown Attribute Weights

For decision-making matters of major public livelihood with unknown attribute weights, a multi-attribute large group decision-making method based on public dual valuation is proposed. Firstly, attribute values and overall performance over different alternatives are determined based on the dual evaluation given by the public. Secondly, two kinds of correlation degrees are calculated separately: one is the correlation degree between attribute values and approval ratings, the other is the correlation degree between attribute values and non-approval ratings. According to the two measurement results of correlation degrees, the interval of attribute weights is determined. Thirdly, an optimization model is established with the objective of minimizing attribute deviations over all alternatives to obtain the attribute weights. The TOPSIS method is used to sort the alternatives and determine the optimal one. Finally, a numerical example is given to verify the proposed method in this paper. Verification results of the numerical example indicate that the method proposed in this paper can integrate public evaluation information into the decision-making process, which determines relevant decision-making information and attribute weights accordingly, ensuring that the decision results can fully reflect public opinions and guaranteeing decision effectiveness.