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Extension Of The Expected Value Method For Multiple Attribute Decision Making With Fuzzy Data

机译:模糊数据的多属性决策中期望值方法的扩展

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This paper is concerned with a method for multiple attribute decision making under fuzzy environment,in which the preference values take the form of triangular fuzzy numbers.Based on the idea that the attribute with a larger deviation value among alternatives should be assessed a larger weight,a linear programming model about the maximal deviation of weighted attribute values is established.Therefore,an approach to deal with attribute weights which are completely unknown is developed by using expected value operator of fuzzy variables.Furthermore,in order to make a decision or choose the optimum alternative,an expected value method is presented under the assumption that attribute weights are known fully.The method not only avoids complex comparing for fuzzy numbers,but also has the advantages of simple operation and easy calculation.Finally,a numerical example is used to illustrate the proposed approach at the end of this paper.
机译:本文涉及一种模糊环境下的多属性决策方法,其中偏好值采用三角模糊数的形式。基于这样的想法,即在备选方案之间具有较大偏差值的属性应被评估为更大的权重,建立了关于加权属性值最大偏差的线性规划模型。因此,通过使用模糊变量的期望值算子,开发了一种处理属性权完全未知的方法。最优选择,在充分考虑属性权重的前提下提出了一种期望值方法。该方法不仅避免了模糊数的复杂比较,而且具有操作简单,计算容易的优点。在本文末尾说明拟议的方法。

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