2026-09-15T17:15:25Zhttps://gredos.usal.es/oai/request

oai:gredos.usal.es:10366/1574352025-04-30T20:38:57Zcom_10366_68584com_10366_4512com_10366_3823col_10366_68585

00925njm 22002777a 4500 dc Zulqarnain, Rana Muhammad author Naveed, Hamza author Siddique, Imran author Alcantud, José Carlos R. author 2024-07 [EN] The selection of a reliable and competent transportation company is a typical multi-criteria group decision- making (MCGDM) challenge in supply chain management. MCGDM has been widely used for decision support under ambiguity and uncertainty. This paper considers this problem in the setting of interval-valued q-rung orthopair fuzzy soft sets (IVq-ROFSS), a novel extension of fuzzy sets that presents an integrated approach to interpreting imperfect and ambiguous data. This study explores the novel Einstein aggregation operators (AOs) for this model, specifically the interval-valued q-rung orthopair fuzzy soft Einstein weighted average (IVq-ROFSEWA) and interval-valued q-rung orthopair fuzzy soft Einstein weighted geometric (IVq-ROFSEWG). These operators can consider large amounts of data that include all connections among parameters. Their fundamental properties (such as idempotency, boundedness, homogeneity, monotonicity, and shift invariance) are presented and proven. With the assistance of the new Einstein AOs, we design a novel MCGDM approach. A case study is presented to choose the most reliable transportation company that endorses the rationality and credibility of the proposed decision-making technique in supply chain management. Hence, this research helps with an innovative decision-support structure for assessing transport corporations. Zulqarnain, R. M., Naveed, H., Siddique, I., & Alcantud, J. C. R. (2024). Transportation decisions in supply chain management using interval-valued q-rung orthopair fuzzy soft information. Engineering Applications of Artificial Intelligence, 133, 108410. https://doi.org/10.1016/j.engappai.2024.108410 0952-1976 1873-6769 http://hdl.handle.net/10366/157435 10.1016/j.engappai.2024.108410 Interval-valued q-rung orthopair fuzzy soft sets Einstein aggregation operators MCGDM Transportation Supply chain management Transportation decisions in supply chain management using interval-valued q-rung orthopair fuzzy soft information