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首页> 外文期刊>Fuzzy Optimization and Decision Making: A Journal of Modeling and Computation Under Uncertainty >A group decision making with probability linguistic preference relations based on nonlinear optimization model and fuzzy cooperative games
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A group decision making with probability linguistic preference relations based on nonlinear optimization model and fuzzy cooperative games

机译:基于非线性优化模型和模糊合作游戏的概率语言偏好关系群决策

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摘要

The aim of the paper is to solve the group decision making problems which contain inconsistent probabilistic linguistic preference relations (PLPRs) and unknown expert weights. When the PLPRs are inconsistent, there are contradictories in the preference relations expressed by the experts. The evaluation value with contradictory information will bring out an incorrect consequence in decision making. Hence, this paper develops a novel consistency measure method to gauge the consistency level of PLPRs. Moreover, a nonlinear optimization model is newly constructed to optimize the inconsistent PLPRs. The proposed methods overcome the limitations in the existing methods and ameliorate the interpretation and complexities of inconsistency PLPRs revise strategies. Additionally, a weighting method using fuzzy cooperative games with PLPRs is put forward to derive the weight vector of experts. It helps to balance the deviations between the individual PLPRs and the group PLRP. At last, a numerical example illustration for physician selection is put forward to demonstrate the effectiveness of the proposed model and its practical applicability. The comparative analysis gives deep insights into the rationality of the proposed model.
机译:本文的目的是解决群体决策,其中包含不一致的概率语言偏好关系(PLPRS)和未知的专家权重。当PLPRS不一致时,专家表达的偏好关系中存在矛盾。具有矛盾信息的评估价值将对决策产生不正确的后果。因此,本文开发了一种新的一致性测量方法来衡量PLPRS的一致性水平。此外,新建非线性优化模型以优化不一致的PLPR。拟议的方法克服了现有方法的局限性,并改善了不一致的PLPRS修改战略的解释和复杂性。另外,提出了一种使用PLPRS模糊协作游戏的加权方法来导出专家的重量向量。它有助于平衡各个PLPRS与Group PLRP之间的偏差。最后,提出了医生选择的数值示例图,以证明所提出的模型的有效性及其实际适用性。比较分析对拟议模型的合理性提供了深入的见解。

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