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Multiple-attribute decision-making method based on the correlation coefficient between dual hesitant fuzzy linguistic term sets

机译:基于双重犹豫模糊语言术语集之间相关系数的多属性决策方法

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摘要

Hesitant fuzzy linguistic term sets (HFLTS) and dual hesitant fuzzy sets (DHFS) are two important branches of fuzzy mathematics, both of which have been widely applied in multiple-attribute decision-making (MADM) problems under uncertain environments. To humanize the decision-making process, the former deals with hesitant fuzzy linguistic terms in line with people's common sense, and to reflect the nature of people's hesitancy, the latter deals with both the membership and nonmembership hesitancy functions of fuzzy sets (FS). However, as the decision-making environment is increasingly complex, the characteristics of these two sets need to be combined to more precisely represent the fuzzy linguistic information. Therefore, this paper proposes a new extension of the HFLTS concept, i.e., dual hesitant fuzzy linguistic term set (DHFLTS), to highlight the importance of the nonmembership degree for HFLTSs. Some properties for the DHFLTS are given. Motivated by information energy, the information energy for DHFLTS and the correlation coefficient between DHFLTSs as well as the weighted correlation coefficient are defined. Finally, a supplier selection problem is given to demonstrate the feasibility and superiority of this method.
机译:犹豫模糊语言术语集(HFLTS)和对偶犹豫模糊集(DHFS)是模糊数学的两个重要分支,二者都已广泛应用于不确定环境下的多属性决策(MADM)问题。为了使决策过程人性化,前者根据人们的常识来处理犹豫的模糊语言术语,并反映人们犹豫的性质,后者则处理模糊集(FS)的隶属和非隶属犹豫功能。但是,随着决策环境的日益复杂,需要将这两套系统的特征结合起来,以更精确地表示模糊语言信息。因此,本文提出了HFLTS概念的新扩展,即双重犹豫模糊语言术语集(DHFLTS),以突出非成员程度对HFLTS的重要性。给出了DHFLTS的一些属性。在信息能量的激励下,定义了DHFLTS的信息能量,DHFLTS之间的相关系数以及加权相关系数。最后,给出了一个供应商选择问题,以证明该方法的可行性和优越性。

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