As a more flexible and practical approach than the Pythagorean fuzzy set and intuitionistic fuzzy set, the q-rung orthopair fuzzy set (q-ROFS) has been widely used to express vagueness and uncertainty. In this paper, a method based on a weighted induced logarithmic distance is presented to help address multiple attribute decision making (MADM) with q-ROFS information. A new induced weighted logarithmic distance measure is first proposed to remedy the shortcomings of existing methods. Some outstanding properties have also been examined in detail. Considering the superiority of q-ROFS in modeling uncertainties, the improved induced weighted logarithmic distance measure is then extended to q-ROFS, thereby obtaining two new q-ROFS distance measures. Moreover, based on the developed q-ROFS distance measures, a new method for handling MADM problems under q-ROFS environment is presented, wherein information concerning the attribute weights is completely unknown. Finally, a numerical example concerning smart phone selection is presented to demonstrate the validity and superiority of the proposed method.

作为比勾股定模糊集和直觉模糊集更灵活，更实用的方法，q阶邻对模糊集（q-ROFS）已被广泛用于表达模糊性和不确定性。本文提出了一种基于加权对数距离的方法，以帮助解决带有q-ROFS信息的多属性决策（MADM）。首先提出了一种新的归纳加权对数距离度量，以弥补现有方法的不足。还对一些出色的性能进行了详细检查。考虑到q-ROFS在建模不确定性方面的优势，改进的诱导加权对数距离度量随后扩展到q-ROFS，从而获得了两个新的q-ROFS距离度量。此外，根据已开发的q-ROFS距离度量，提出了一种在q-ROFS环境下处理MADM问题的新方法，其中关于属性权重的信息是完全未知的。最后，给出了一个关于智能手机选择的数值例子，以证明该方法的有效性和优越性。