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Bonferroni mean operators of generalized trapezoidal hesitant fuzzy numbers and their application to decision-making problems
Soft Computing ( IF 4.1 ) Pub Date : 2021-01-11 , DOI: 10.1007/s00500-020-05504-4
Irfan Deli

Generalized trapezoidal hesitant fuzzy numbers are useful when ever there is indecision among several possible values for the preferences over objects in the process of decision making. In this sense, the aim of this work is to investigate the multiple attribute decision-making problems with generalized trapezoidal hesitant fuzzy numbers (GTHF-numbers). Therefore, we develop two aggregation techniques called generalized trapezoidal hesitant fuzzy Bonferroni arithmetic mean operator and generalized trapezoidal hesitant fuzzy Bonferroni geometric mean operator for aggregating the generalized trapezoidal hesitant fuzzy information. Then, we examine its properties and discuss its special cases. Also, we develop two approach for multiple attribute decision making under the generalized trapezoidal hesitant fuzzy environments. Also, we apply the proposed approaches based on Bonferroni aggregation operators under generalized trapezoidal hesitant fuzzy environments to multicriteria decision making, and we give two practical example to illustrate our results. In the end, we give an analysis of the proposed approaches by providing a brief comparative analysis of these methods with existing methods.



中文翻译:

Bonferroni广义梯形犹豫模糊数的均值算子及其在决策问题中的应用

当在决策过程中对对象的偏爱的几个可能值之间不确定时,广义梯形犹豫模糊数很有用。从这个意义上讲,这项工作的目的是研究具有广义梯形犹豫模糊数(GTHF数)的多属性决策问题。因此,我们开发了两种聚集技术,分别用于广义梯形犹豫模糊Bonferroni算术平均算子和广义梯形犹豫模糊Bonferroni几何均值算子,以聚合广义梯形犹豫模糊信息。然后,我们检查其属性并讨论其特殊情况。此外,我们开发了两种在广义梯形犹豫模糊环境下进行多属性决策的方法。也,我们在广义梯形犹豫模糊环境下将基于Bonferroni聚合算子的拟议方法应用于多准则决策,并给出两个实际的例子来说明我们的结果。最后,我们通过对这些方法与现有方法进行简要的比较分析来对所提出的方法进行分析。

更新日期:2021-01-11
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