属性权重未知情形下基于公众双重评价的多属性大群体决策方法

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

    • 摘要: 针对属性权重未知的重大民生决策事项,提出了一种基于公众双重评价的多属性大群体决策方法。首先,根据公众给出的双重评价信息确定各方案的属性值和整体表现情况。然后分别计算各方案属性值与认可度之间、属性值与非认可度之间的关联水平,根据两类关联度测度结果确定属性权重的取值区间。以所有方案属性值的信息离差度最小化为目标构建优化模型确定属性权重。利用TOPSIS法对方案进行排序,确定最优方案。最后通过算例对本文提出的方法进行验证。根据算例验证结果可知,本文提出的方法可以将公众评价信息融入决策活动之中,以此为依据确定相关决策信息和属性权重,使得决策结果能够充分反映民意,确保决策的有效性。

       

      Abstract: 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.

       

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