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An approach to multi-attribute group decision making based on multigranulation probabilistic fuzzy rough set and Multimoora method

机译:一种基于多个人概率模糊粗糙集和多国制粗粗套和多国制作方法的多属性组决策方法

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This paper proposes a new approach to uncertainty multiple attribute group decision problem with linguistic preference relation based on multigranulation probabilistic rough set and the Multimoora method. According to the classical Pawlak rough set and the neighborhood rough set, we present a multigranulation probabilistic fuzzy rough set based on neighborhood relation with linguistic preference information. We investigate the rough approximation of a crisp decision-making object and a fuzzy decision-making object under the framework of multigranulation rough set theory with linguistic preference inforamtion, respectively. That is, a multigranulation probabilistic rough set model and a multigranulation probabilistic fuzzy rough set model based on delta-neighborhood relation are established, respectively. Meanwhile, the proposed multigranulation probabilistic fuzzy rough set model is compared with the existing model and illustrate the superiority of the new model established. Furthermore, by combining the multigranulation probabilistic fuzzy rough set and the Multimoora method, a new method for multiple attribute group decision making with linguistic preference information is proposed. The decision-making procedure and the algorithm of the proposed method are also given. Finally, the effectiveness and validity of the proposed method is verified by investigating a multiple attribute group decision problem with the selection of suppliers in the context of e-commerce.
机译:本文提出了一种基于多个人概率粗糙集的语言偏好关系的不确定度多属性组决策问题。根据古典的佩加拉克粗糙集和邻域粗糙集,我们提出了一种基于与语言偏好信息的邻域关系的多个人概率模糊粗糙集。我们分别调查了脆性决策对象的粗略近似,分别根据语言偏好Inforamtion的多个人粗糙集理论框架下的模糊决策对象。也就是说,建立了一种基于三角洲关系关系的多个人概率粗糙集模型和多个人概率模糊粗糙集模型。同时,将所提出的多个人概率模糊粗糙集模型与现有模型进行比较,并说明了建立的新模型的优越性。此外,通过组合多个人概率模糊粗糙集和多国处理方法,提出了一种利用语言偏好信息的多个属性组决策的新方法。还给出了所提出的方法的决策程序和算法。最后,通过在电子商务的背景下选择供应商的选择来验证所提出的方法的有效性和有效性。

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