Normal wiggly hesitant fuzzy set (NWHFS) is a new fuzzy information form to help decision makers (DMs) express their evaluations, which can further dig the potential uncertain information hidden in the original data given by the DMs. Firstly, we define a new distance measure and new operational laws of NWHFSs. Then, for the situation where attribute weights are completely unknown, we propose an extended CCSD method to produce them objectively, which comprehensively uses standard deviation (SD) and correlation coefficient (CC). What's more, we introduce the MABAC (multiattributive border approximation area comparison) method, which takes the distance between alternatives and the border approximation area (BAA) into consideration for handling the complex and uncertain decision‐making problems. Meanwhile, we combine the MABAC method with prospect theory (PT), which considers DMs' psychological behavior, and propose a new NWHF‐CCSD‐PT‐MABAC method to cope with the multi‐attribute decision making problems under normal wiggly hesitant fuzzy environment. Lastly, we illustrate the validity and advantages of the proposed method through an example of college book supplier selection.

中文翻译：

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基于CCSD和前景理论的多属性决策正态摆动犹豫模糊MABAC方法

正态摆动犹豫模糊集（NWHFS）是一种新的模糊信息形式，可以帮助决策者（DM）表达他们的评价，可以进一步挖掘决策者给出的原始数据中隐藏的潜在不确定信息。首先，我们定义了 NWHFS 的新距离度量和新运行规律。然后，针对属性权重完全未知的情况，我们提出了一种综合使用标准差（SD）和相关系数（CC）的扩展CCSD方法来客观地产生它们。更重要的是，我们引入了MABAC（多属性边界近似区域比较）方法，该方法考虑了备选方案与边界近似区域（BAA）之间的距离来处理复杂和不确定的决策问题。同时，我们将MABAC方法与考虑DMs心理行为的前景理论（PT）相结合，提出了一种新的NWHF-CCSD-PT-MABAC方法来应对正常摆动犹豫模糊环境下的多属性决策问题。最后，我们通过一个大学图书供应商选择的例子来说明所提出方法的有效性和优势。