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Estimating the missing values for the incomplete decision matrix and consistency optimization in emergency management

机译：估计不完整决策矩阵的缺失值和应急管理中的一致性优化

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摘要

Unconventional emergency decision making not only involves intangible and conflicting criteria, but also needs a fast response to the emergency incident under the cases of time pressure and incomplete information. It might be an effective way to make full use of the outlier data of incident information and skip some direct comparisons between alternatives to make a fast emergency decision. Focusing on the missing judgments estimation issue in an incomplete comparison emergency decision matrix, this paper extends the geometric mean induced bias matrix to estimate the missing judgments and improve the consistency ratios at the same time. The least absolute error method and the least square method are used to optimize the revised geometric mean induced bias matrix and find the missing values. A numerical example with incomplete information is used to demonstrate the proposed models. A case of emergency decision making simulation is also conducted to show how the proposed model is applied in practice. The results show the proposed models are not only capable of completing missing values, but also can efficiently improve the matrix consistency at the same time. In addition, the proposed model can aid emergency managers to make a fast response to unconventional emergency in the case of lacking complete information.
机译：非常规的紧急决策不仅涉及无形和冲突的标准，而且在时间紧迫和信息不完整的情况下，还需要对紧急事件做出快速响应。充分利用事件信息的异常数据并跳过替代方案之间的一些直接比较以做出快速紧急决策可能是一种有效的方法。针对不完全比较紧急决策矩阵中的缺失判断估计问题，本文扩展了几何均值偏差矩阵，以估计缺失判断，同时提高了一致性比率。最小绝对误差法和最小二乘法用于优化修正的几何均值诱导偏差矩阵并找到缺失值。带有不完整信息的数值示例用于说明所提出的模型。还进行了一个紧急决策仿真案例，以说明所提出的模型如何在实践中应用。结果表明，所提出的模型不仅能够完成缺失值，而且可以有效地提高矩阵的一致性。此外，在缺乏完整信息的情况下，所提出的模型可以帮助应急管理人员对非常规紧急情况做出快速响应。

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