A novel decision support system for sustainable logistics management in interval-valued fermatean picture fuzzy structure.

Umar Ali, Junxiang Li, Qin Qi, Usman Zulfiqar, Taha Radwan, Imran Siddique, Rana Muhammad Zulqarnain

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Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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7 authors.

Umar AliBusiness School, University of Shanghai for Science and Technology, Shanghai, 200093, China.

Junxiang LiBusiness School, University of Shanghai for Science and Technology, Shanghai, 200093, China.

Qin QiDepartment of Publishing and Dissemination, Shanghai Publishing and Printing College, Shanghai, 200093, China.

Usman ZulfiqarDepartment of Business Administration, Lahore Leads University, Lahore, Pakistan.

Taha RadwanDepartment of Management Information Systems, College of Business and Economics, Qassim University, 51452, Buraydah, Saudi Arabia. t.radwan@qu.edu.sa.

Imran SiddiqueDepartment of Mathematics, University of Sargodha, Sargodha, 40500, Pakistan.

Rana Muhammad ZulqarnainDepartment of Mathematics, Saveetha School of Engineering, SIMATS Thandalam, Chennai, Tamil Nadu, 602105, India.

Funding

Deanship of Graduate Studies and Scientific Research at Qassim University QU-APC-2025

6 · The paper itself

Abstract

Determining a sustainable logistics management system constitutes an extensive decision-making process characterized by fundamental volatility. Interval-valued Fermatean picture fuzzy sets (IVFPFS) propose a more versatile and detailed structure to represent obscure and unreliable data, making them more suitable for such concerns. Each possibility in this structure is examined based on significant criteria, including infrastructure development, logistics, economic performance, operational management, and technological innovation. This study describes and analyses the properties of two proficient aggregation operators: the interval-valued Fermatean picture fuzzy Einstein weighted average (IVFPFEWA) and the interval-valued Fermatean picture fuzzy Einstein weighted geometric (IVFPFEWG) operators. A new multi-attribute decision-making (MADM) methodology is presented, implementing Einstein-based operators in an IVFPFS structure to boost decision-making procedures for sustainable logistics management. The comparative and sensitivity analyses confirm the consistency and potency of the presented strategy, indicating that it remains more realistic and functional than conventional strategies. The outcomes demonstrate that the laid out technique delivers a realistic decision to the obstacles of maintaining a resilient logistics system.

Indexed as

Decision makingEinstein aggregation operatorsInterval-valued Fermatean picture fuzzy setLogistic management systemMADM

Identifiers

PMID40883326

DOI10.1038/s41598-025-06699-y

PMCPMC12397336

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