Multi-Attribute Group Decision Making Based on a New Ranking of Positive and Negative Interval Type-2 Fuzzy Numbers

نویسندگان

1 ‎Department of Industrial Engineering‎, ‎Payame Noor University‎, ‎Iran‎.‎‎

2 ‎Department of Industrial Engineering‎, ‎Payame Noor University‎, ‎Iran‎.‎‎

doi
10.30473/coam.2025.74715.1311
چکیده

This paper addresses multi-attribute group decision-making (MAGDM) where linguistic assessments are represented by both positive and negative interval type-2 fuzzy numbers (IT2FNs)‎, ‎capturing the intrinsic uncertainty of group evaluations more accurately. ‎We introduce a novel ranking method for IT2FNs that simultaneously utilizes the mean and standard deviation of the upper and lower membership functions‎, ‎ as well as the IT2FN's height‎. ‎This enhances its discriminatory capability‎. ‎The theoretical foundations of this ranking— encompassing zero‎, ‎unity‎, ‎and symmetry properties— are rigorously established‎, ‎and its superiority over existing techniques is demonstrated through comparative analyses on seven benchmark datasets‎. ‎Building on this ranking‎, ‎we develop an integrated fuzzy MAGDM framework that can handle both positive and negative IT2FN assessments for criteria and weights‎. ‎The framework’s practicality and effectiveness are validated through two case studies‎: ‎one with exclusively positive linguistic terms and another with mixed positive and negative scales‎. ‎Results indicate that the proposed ranking and decision framework yield more rational and robust group decisions under substantial uncertainty‎. ‎They outperform conventional fuzzy methods and offer a nuanced solution for real-world MAGDM scenarios‎.