In the article, we establish two multiple attribute decision making (MADM) approaches using the developed weighted generalized Maclaurin symmetric mean (q-ROFWGMSM) and weighted generalized geometric Maclaurin symmetric mean (q-ROFWGGMSM) operator concerning q-rung orthopair fuzzy numbers (q-ROFNs). Firstly, inspired by the generalized Maclaurin symmetric mean (G-MSM) and geometric Maclaurin symmetric mean (Geo-MSM) operators, we establish the q-rung orthopair fuzzy G-MSM (q-ROFGMSM) and q-rung orthopair fuzzy Geo-MSM (q-ROFGGMSM) operators, which assumes the grades of membership and non-membership to evaluate information can take any values in interval [0,1] respectively and the attributes are relevant to other multiple attributes. Then, we present its characteristics and some special cases. Moreover, we propose the weighted forms of the q-ROFGMSM and q-ROFGGMSM operator, which is called the q-ROFWGMSM and q-ROFWGGMSM operators, respectively. Then, we present their some characteristics and special examples. Finally, we put forward two new MADM approaches founded on the developed q-ROFWGMSM and q-ROFWGGMSM operators. The developed approaches are more general and more practicable than Liu and Wang's MADM approach (2018), Wei and Lu's MADM method (2017), Qin and Liu's MADM method (2014) and Shen et al.’s MADM approach (2018).

在本文中，我们使用q阶正交对对模糊数（q）的加权加权广义Maclaurin对称均值（q-ROFWGMSM）和加权广义几何Maclaurin对称均值（q-ROFWGGMSM）算符建立了两种多属性决策（MADM）方法。 -ROFN）。首先，根据广义Maclaurin对称均值（G-MSM）和几何Maclaurin对称均值（Geo-MSM）算子的启发，我们建立了q阶正交对对模糊G-MSM（q-ROFGMSM）和q阶正交对对模糊Geo- MSM（q-ROFGGMSM）运算符（假定用于评估信息的成员资格和非成员资格的等级）可以分别采用间隔[0,1]中的任何值，并且该属性与其他多个属性相关。然后，我们介绍其特点和一些特殊情况。此外，我们提出q-ROFGMSM和q-ROFGGMSM运算符的加权形式，分别称为q-ROFWGMSM和q-ROFWGGMSM运算符。然后，我们介绍它们的一些特征和特殊示例。最后，我们基于已开发的q-ROFWGMSM和q-ROFWGGMSM运算符，提出了两种新的MADM方法。与Liu和Wang的MADM方法（2018），Wei and Lu的MADM方法（2017），Qin和Liu的MADM方法（2014）和Shen等人的MADM方法（2018）相比，已开发的方法更为通用和实用。