Q-rung orthopair fuzzy weighted induced logarithmic distance measures and their application in multiple attribute decision making

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.

Automated summary

This paper introduces a new method based on weighted induced logarithmic distance to address multiple attribute decision making with q-rung orthopair fuzzy set (q-ROFS) information, and extends it to q-ROFS distance measures for situations where attribute weights are unknown.