An Integrated Multi-Objective Optimization Ratio Analysis Plus Full Multiplicative form Method with Linguistic Generalized Orthopair Fuzzy Sets for Decision-Making

• Published in: International journal of applied and computational mathematics Vol. 11; no. 4
• Main Authors: Khan, Ayesha, Ahmad, Uzma
• Format: Journal Article
• Language: English
• Published: New Delhi Springer India 01.08.2025; Springer Nature B.V
• Subjects: Applications of Mathematics; Computational Science and Engineering; Decision making; Fuzzy sets; Linguistics; Mathematical and Computational Physics; Mathematical Modeling and Industrial Mathematics; Mathematics; Mathematics and Statistics; Multiple objective analysis; Nuclear Energy; Operations Research/Decision Theory; Optimization; Original Paper; Qualitative analysis; Salience; Theoretical; MULTIMOORA method; Alternatives; MAGDM; Asian Infrastructure Investment Bank
• ISSN: 2349-5103; 2199-5796
• DOI: 10.1007/s40819-025-01987-7

Linguistic q -rung orthopair fuzzy sets (L q -ROFSs) are extended versions of different sets accommodating their salient features, which are efficient and important tools for representing and tackling information in the real-world decision-making (DM) issues involving uncertainty. Furthermore, linguistic variables (LVs) have significant importance in representing the qualitative nature of data during the judgement process. L q -ROFS is composed of two linguistic membership degrees and satisfies the condition that the sum of its degrees to the power of q is less than or equal to 1. In this paper, our main target is to initiate a new method on the grounds of multi-objective optimization ratio analysis plus a full multiplicative form (MULTIMOORA) method to cope with the arising DM problems. Inspired by linguistic evaluations and the broader structure of L q -ROFS and the effectiveness of the MULTIMOORA approach to cope with the linguistic uncertain problems, we successfully developed the L q -ROF-MULTIMOORA approach. The proposed model is verified by the two numerical instances of group DM. To address the feasibility and practicality of the novel methodology, we compare it with the linguistic Pythagorean fuzzy TOPSIS method.