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<p>Determining a sustainable food supplier is a decision-making problem with inherent uncertainty. The interval-valued Pythagorean fuzzy soft set (IVPFSS) is a type of fuzzy set that provides a wider range of solutions for presenting fuzzy and unreliable data. Therefore, every alternative is determined by evaluating multiple factors, including community involvement, staff health, financial stability, fostering imaginative thinking, business growth, minimizing carbon footprints, eliminating waste, and composting. This research mainly describes the interval-valued Pythagorean fuzzy soft Einstein-ordered weighted and Einstein hybrid weighted aggregation operators (AOs). The Evaluation based on the Distance from the Average Solution (EDAS) is a unique decision-making method that uses proposed aggregation operators to address multi-attribute group decision-making (MAGDM) problems. Implementing the proposed strategy substantially influences the selection of the most economical food supply chain management supplier. The practicability of our recommended approach is demonstrated through an empirical investigation focused on identifying a particularly productive vendor in the organic food sector. Comparative and sensitivity analysis reflect the predictability and efficacy of this approach and determine that the planned methodology is more realistic and feasible than conventional methods. The outcomes indicate that the proposed strategy offers a viable solution to address the challenges of sustainable food supplier selection (SFSS) with unclear facts.</p>

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An extended EDAS model for sustainable supplier selection in food supply chain management using interval-valued Pythagorean fuzzy soft set

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月27日

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  • Rana Muhammad Zulqarnain,
  • Hamza Naveed,
  • Hassan Naseer,
  • Rifaqat Ali,
  • Abdullatif Ghallab,
  • Imran Siddique,
  • Sohaib Abdal

摘要

Determining a sustainable food supplier is a decision-making problem with inherent uncertainty. The interval-valued Pythagorean fuzzy soft set (IVPFSS) is a type of fuzzy set that provides a wider range of solutions for presenting fuzzy and unreliable data. Therefore, every alternative is determined by evaluating multiple factors, including community involvement, staff health, financial stability, fostering imaginative thinking, business growth, minimizing carbon footprints, eliminating waste, and composting. This research mainly describes the interval-valued Pythagorean fuzzy soft Einstein-ordered weighted and Einstein hybrid weighted aggregation operators (AOs). The Evaluation based on the Distance from the Average Solution (EDAS) is a unique decision-making method that uses proposed aggregation operators to address multi-attribute group decision-making (MAGDM) problems. Implementing the proposed strategy substantially influences the selection of the most economical food supply chain management supplier. The practicability of our recommended approach is demonstrated through an empirical investigation focused on identifying a particularly productive vendor in the organic food sector. Comparative and sensitivity analysis reflect the predictability and efficacy of this approach and determine that the planned methodology is more realistic and feasible than conventional methods. The outcomes indicate that the proposed strategy offers a viable solution to address the challenges of sustainable food supplier selection (SFSS) with unclear facts.