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A hesitant fuzzy multiple attribute decision making method based on linear programming and TOPSIS *

机译:一种基于线性规划和TOPSIS的犹豫的模糊多属性决策方法。 *

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Hesitant fuzzy set (HFS) provides an effective tool in dealing with decision making situation when only some values of a membership are possible for an alternative on certain attribute. In this paper, we propose a method based on linear programming and TOPSIS to solve the multiple attribute decision making (MADM) problem with partially known attribute weight information under hesitant fuzzy environment. To begin with, we present a linear programming model for assessing objective attribute weights from the decision making matrix and partially known attribute weight information. Moreover, we utilize the weighted correlation coefficient values between every alternative and the positive ideal point to rank all the alternatives based on TOPSIS. Furthermore, a numerical example is utilized to validate the MADM method proposed in this paper.
机译:当仅某些成员资格的值可能替代某些属性时,犹豫模糊集(HFS)提供了一种有效的工具来处理决策情况。本文提出了一种基于线性规划和TOPSIS的方法,以解决在不确定的模糊环境下具有部分已知属性权重信息的多属性决策(MADM)问题。首先,我们提出一个线性规划模型,用于从决策矩阵和部分已知的属性权重信息中评估目标属性权重。此外,我们利用每个备选方案与正理想点之间的加权相关系数值对基于TOPSIS的所有备选方案进行排名。此外,通过数值算例验证了本文提出的MADM方法。

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