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Multi‐criteria group decision‐making method based on TODIM with probabilistic interval‐valued hesitant fuzzy information

机译:基于TODIM的概率区间值犹豫模糊信息的多准则群决策方法

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Probabilistic interval-valued hesitant fuzzy sets (PIV-HFSs) are suitable for aggregating information from different groups because the probabilistic information of all the groups can be included by using interval values. Moreover, decision makers (DMs) prefer to use interval values to provide evaluation information. Furthermore, the traditional multi-criteria group decision-making (MCGDM) approach has some limitations, such as obtaining the DMs' weights with inappropriate methods and neglecting the interactions amongst the criteria and the psychological characteristics of DMs. Motivated by these research background, the main contents of this study are as follows. First, PIV-HFSs are proposed, and the convex combination operation is extended into PIV-HFSs. Second, a hybrid MCGDM approach with PIV-HFSs is suggested that is based on the maximizing deviation method, fuzzy analytic network process (FANP) and TODIM (an acronym in Portuguese for interactive and multi-criteria decision-making model). Third, an evaluation case of health management centres based on the service-specific failure mode and effect analysis (FMEA) is considered. The results show that the most crucial secondary factor is frequency (0.35775) and that the most serious failure mode is the inaccurate check-in. The results demonstrate that the proposed model can evaluate service quality effectively and that it performs better than other methods.
机译:概率间隔值犹豫模糊集(PIV-HFS)适用于汇总来自不同组的信息,因为可以使用间隔值来包含所有组的概率信息。此外,决策者(DM)更喜欢使用间隔值来提供评估信息。此外,传统的多准则群体决策(MCGDM)方法还存在一些局限性,例如使用不合适的方法获得决策者的权重,而忽略决策者的准则和心理特征之间的相互作用。基于这些研究背景,本研究的主要内容如下。首先,提出了PIV-HFS,并将凸组合运算扩展为PIV-HFS。其次,提出了一种基于PIV-HFS的混合MCGDM方法,该方法基于最大偏差法,模糊分析网络过程(FANP)和TODIM(葡萄牙语为交互式和多标准决策模型的首字母缩写)。第三,考虑了基于特定服务故障模式和效果分析(FMEA)的健康管理中心评估案例。结果表明,最关键的次要因素是频率(0.35775),而最严重的故障模式是不准确的登机。结果表明,该模型可以有效地评估服务质量,并且比其他方法具有更好的性能。

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