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A novel intuitionistic fuzzy Yager aggregation framework for decision making in green supply chains
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  • Published: 13 February 2026

A novel intuitionistic fuzzy Yager aggregation framework for decision making in green supply chains

  • Yeshvandhini Kumar  ORCID: orcid.org/0009-0000-5142-12761,
  • Sujatha Ramalingam  ORCID: orcid.org/0000-0002-3379-67761 &
  • Gizachew Bayou Zegeye  ORCID: orcid.org/0000-0001-6225-99052 

Scientific Reports , Article number:  (2026) Cite this article

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  • Engineering
  • Mathematics and computing

Abstract

Aggregation operators constitute the core mathematical mechanism of multi-criteria decision-making by integrating multiple attribute evaluations into a single representative assessment. However, in intuitionistic fuzzy environments characterized by uncertainty, vagueness, and human hesitation, many existing aggregation operators inadequately capture nonlinear interactions among criteria and often weaken the influence of hesitancy information during aggregation. This paper examines the role of Yager-based aggregation mechanisms in preserving the structural integrity of intuitionistic fuzzy information and improving decision reliability under ambiguous conditions. A comprehensive family of Yager-based intuitionistic fuzzy aggregation operators is developed for multi-attribute decision-making problems, including weighted, ordered weighted, hybrid weighted averaging, and corresponding geometric operators. The principal advantage of the proposed operators lies in their flexible control of conjunction and disjunction behaviour through Yager’s t-norm and t-conorm, which enables a more balanced treatment of truth, indeterminacy, and falsity degrees compared with existing approaches. The system achieves logical stability through its core axiomatic properties which include idempotency and monotonicity and boundedness and commutativity. The framework shows stable ranking results which produce understandable outputs that identify differences between options during the selection process of eco-friendly companies in green supply chain management. The results show that Yager-based intuitionistic fuzzy aggregation creates a strong decision-support system which helps users make sustainable choices in complicated industrial ecosystems.

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Author information

Authors and Affiliations

  1. Mathematics, School of Science and Humanities, Shiv Nadar University Chennai, Rajiv Gandhi Salai (OMR), Kalavakkam, Chengalpattu District, Tamil Nadu, 603110, India

    Yeshvandhini Kumar & Sujatha Ramalingam

  2. Department of Mathematics, Bahir Dar University, P.O. Box,79, Bahir Dar, Ethiopia

    Gizachew Bayou Zegeye

Authors
  1. Yeshvandhini Kumar
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  2. Sujatha Ramalingam
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  3. Gizachew Bayou Zegeye
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Contributions

All authors contributed to the study conception and design. Conceptualization, Formal Analysis, Investigation, Data Curation, Writing-Original Draft were performed by YK and SR; Resources and Supervision, SR. Methodology, YK, SR and GBZ. Writing-Review &Editing, Visualization, SR and GBZ. All authors have read and agreed to the published version of the manuscript.

Corresponding authors

Correspondence to Sujatha Ramalingam or Gizachew Bayou Zegeye.

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Kumar, Y., Ramalingam, S. & Zegeye, G.B. A novel intuitionistic fuzzy Yager aggregation framework for decision making in green supply chains. Sci Rep (2026). https://doi.org/10.1038/s41598-026-37890-4

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  • Received: 12 November 2025

  • Accepted: 27 January 2026

  • Published: 13 February 2026

  • DOI: https://doi.org/10.1038/s41598-026-37890-4

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Keywords

  • Intuitionistic fuzzy numbers
  • Yager t-norm and t-conrom
  • Aggregation operators
  • Decision making
  • Green supply chain management
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