Models for multiple attribute decision making with dual hesitant pythagorean fuzzy information

Linggang Ran
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Abstract

In this paper, we investigate the multiple attribute decision making (MADM) problem based on the Muirhead Mean (MM) operators with dual Pythagorean hesitant fuzzy information. Then, motivated by the ideal of MM operators, we have developed some MM operators for aggregating dual hesitant Pythagorean fuzzy information. The prominent characteristic of these proposed operators are studied. Then, we have utilized these operators to develop some approaches to solve the dual hesitant Pythagorean fuzzy multiple attribute decision making problems. Finally, a practical example for supplier selection in supply chain management is given to verify the developed approach and to demonstrate its practicality and effectiveness.
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具有双犹豫毕达哥拉斯模糊信息的多属性决策模型
本文研究了具有双毕达哥拉斯犹豫模糊信息的基于Muirhead均值算子的多属性决策问题。然后,在MM算子理想的激励下,我们开发了一些用于聚合对偶犹豫毕达哥拉斯模糊信息的MM算子。研究了这些算子的显著特性。然后,我们利用这些算子开发了一些方法来解决对偶犹豫毕达哥拉斯模糊多属性决策问题。最后,以供应链管理中的供应商选择为例,验证了该方法的实用性和有效性。
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