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Grey relational analysis method for multiple attribute group decision making based on two-tuple linguistic information

机译:基于二元语言信息的多属性群决策的灰色关联分析方法

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A new method is proposed to solve multiple attribute group decision making problems with linguistic assessment information. In the method, the two-tuple linguistic representation developed in recent years is used to aggregate the linguistic assessment information. According to the traditional ideas of grey relational analysis, the optimal alternative(s) is determined by calculating the linguistic degree of grey relation of every alternative and two-tuple linguistic positive ideal solution and two-tuple linguistic negative ideal solution. It is based on the concept that the optimal alternative should have the largest degree of grey relation from positive ideal solution and the smallest degree of grey relation from the negative ideal solution. The method has exact characteristic in linguistic information processing. It avoided information distortion and losing which occur formerly in the linguistic information processing. Finally, a numerical example is used to illustrate the use of the proposed method. The result shows the approach is simple, effective and easy to calculate.
机译:提出了一种利用语言评估信息解决多属性群决策问题的新方法。在该方法中,使用近年来发展的二元语言表示法来汇总语言评估信息。根据传统的灰色关联分析思想,通过计算每个备选方案的灰色关联的语言程度以及二元语言正理想解和二元语言负理想解来确定最佳替代。基于这样的概念,最佳替代方案应具有与正理想解相比最大的灰度关系,而与负理想解相比具有最小的灰度关系。该方法在语言信息处理中具有确切的特点。它避免了以前在语言信息处理中出现的信息失真和丢失。最后,通过一个数值例子来说明所提出方法的使用。结果表明,该方法简单,有效,易于计算。

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