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Some power Heronian mean operators in multiple attribute decision-making based on q-rung orthopair hesitant fuzzy environment
Journal of Experimental & Theoretical Artificial Intelligence ( IF 2.2 ) Pub Date : 2019-11-26 , DOI: 10.1080/0952813x.2019.1694592
Jie Wang 1 , Ping Wang 2 , Guiwu Wei 1 , Cun Wei 3 , Jiang Wu 3
Affiliation  

ABSTRACT As the generalisation of intuitionistic fuzzy sets (IFSs) and Pythagorean fuzzy set (PFS), the q-rung orthopair fuzzy set (q-ROFS) is more useful to express fuzzy and ambiguous information. Meanwhile, to consider human’s hesitance, the concept of q-rung orthopair hesitant fuzzy set (q-ROHFS) is presented, which can be more valid for handling real multiple attribute decision-making (MADM) problems. To fuse the information in q-ROHFS more effectively, in this article, based on power average (PA) operator and generalised Heronian mean (GHM) operator, some q-rung orthopair hesitant fuzzy power generalised Heronian mean (q-ROHFPGHM) operators which can consider the relationships between being fused arguments are defined and studied. Evidently, the new proposed operators can obtain more exact results than other existing methods. In addition, some precious properties of these operators are discussed. Afterwards, the defined aggregation operators are used to MADM with q-rung orthopair hesitant fuzzy numbers (q-ROHFNs) and the MADM decision-making model is developed. In accordance with the defined operators and built model, the q-rung orthopair hesitant fuzzy weighted power generalised Heronian mean (q-ROHFWPGHM) operator and the q-rung orthopair hesitant fuzzy weighted power generalised geometric Heronian mean (q-ROHFWPGGHM) operator are applied to deal with green supplier selection in supply chain management, and the availability and superiority of the proposed operators are analysed by comparing with some existing approaches. The method presented in this paper can effectually solve the MADM problems which the decision-making information is expressed by q-ROHFNs and the attributes are interactive.

中文翻译:

基于q-rung orthopair犹豫模糊环境的多属性决策中的若干幂Heronian均值算子

摘要 作为直觉模糊集 (IFS) 和勾股模糊集 (PFS) 的泛化,q-梯级正射对模糊集 (q-ROFS) 更适用于表达模糊和歧义信息。同时,为了考虑人的犹豫,提出了q-rung orthopair犹豫模糊集(q-ROHFS)的概念,它可以更有效地处理真实的多属性决策(MADM)问题。为了更有效地融合q-ROHFS中的信息,本文基于功率平均(PA)算子和广义Heronian均值(GHM)算子,提出了一些q-rung orthopair犹豫模糊幂广义Heronian均值(q-ROHFPGHM)算子可以考虑定义和研究被融合参数之间的关系。显然,新提出的算子比其他现有方法可以获得更精确的结果。此外,讨论了这些运算符的一些宝贵属性。然后,将定义的聚合算子用于具有 q-rung orthopair 犹豫模糊数 (q-ROHFNs) 的 MADM,并开发了 MADM 决策模型。根据定义的算子和建立的模型,应用q-rung orthopair犹豫模糊加权幂广义Heronian均值(q-ROHFWPGHM)算子和q-rung orthopair犹豫模糊加权幂广义几何Heronian均值(q-ROHFWPGGHM)算子以应对供应链管理中的绿色供应商选择问题,并通过与现有的一些方法进行比较分析所提出的运营商的可用性和优势。
更新日期:2019-11-26
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