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Group decision making based on the modified probability calculation method and DEA cross-efficiency with probabilistic hesitant fuzzy preference relations

机译:基于修改概率计算方法和DEA交叉效率的组决策与概率犹豫不决的模糊偏好关系

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In this paper, we propose a novel group decision making (GDM) method with probabilistic hesitant fuzzy preference relations (PHFPRs) based on the modified probability calculation method and data envelopment analysis (DEA) cross-efficiency. The primary advantage of the method is that it can reduce information loss and ensure the reliability of the decision-making result. A modified probability calculation method for hesitant fuzzy preference relations (HFPRs) is first proposed to obtain complete and normalized PHFPRs. Then, for the consistent additive preference relation (APR), we construct an output-oriented DEA model to derive the priority vector, in which each alternative is regarded as a decision-making unit (DMU). A DEA cross-efficiency model is further proposed to yield the priority vector, irrespective of whether the desired consistency level is achieved. Furthermore, a stochastic analysis method is developed to obtain the expected priority vector for any PHFPR, and a mathematical programming model is established to obtain the weight vector of decision makers based on group consensus. Finally, the procedure of the GDM method based on the modified probability calculation and the DEA cross-efficiency is designed. We also show the applicability and effectiveness of the proposed GDM method using illustrative examples.
机译:在本文中,我们提出了一种基于修改概率计算方法和数据包络分析(DEA)交叉效率的概率犹豫不决的模糊偏好关系(PHFPRS)的新型组决策(GDM)方法。该方法的主要优点是它可以降低信息损失并确保决策结果的可靠性。首先提出了一种用于犹豫不决的模糊偏好关系(HFPRS)的修改概率计算方法以获得完整和归一化的PHFPRS。然后,对于一致的添加剂偏好关系(APR),我们构建一种以输出导向的DEA模型来得出优先级向量,其中每个替代方案被视为决策单元(DMU)。进一步提出了一种DEA交叉效率模型以产生优先级向量,而不管是否达到所需的一致性水平。此外,开发了一种随机分析方法以获得任何PHFPR的预期优先载体,并且建立了基于组共识的决策者的权重向量来获得数学编程模型。最后,设计了基于修改概率计算和DEA交叉效率的GDM方法的过程。我们还展示了使用说明性示例的所提出的GDM方法的适用性和有效性。

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