ArticleScientific reports2025
Prioritized Aczel-Alsina aggregation operators under p, q-quasirung orthopair fuzzy environment for sustainable supplier selection in new energy vehicle industry.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- A decision aid approach for sports performance evaluation and player activity tracking using fermatean fuzzy Z-information.Scientific reports · 2026Article
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Abstract
Selecting sustainable suppliers in the new energy vehicle industry is a complex decision-making problem due to diverse criteria, uncertainty in evaluations, and the need to prioritize certain factors. Addressing this gap, we propose a novel multi-criteria decision-making (MCDM) framework based on p, q-quasirung orthopair fuzzy ([Formula: see text]ROF) sets and enhanced with Aczel-Alsina-based prioritized aggregation operators. Specifically, we develop two base operators-the [Formula: see text]ROF AA prioritized average ([Formula: see text]ROFAAPA) and the [Formula: see text]ROF AA prioritized geometric ([Formula: see text]ROFAAPG)-along with their weighted prioritized counterparts, the [Formula: see text]ROF AA prioritized weighted average ([Formula: see text]ROFAAPWA) and the [Formula: see text]ROF AA prioritized weighted geometric ([Formula: see text]ROFAAPWG). The mathematical properties of these operators are established, and an MCDM algorithm is formulated to incorporate decision-makers' priority structures. The framework also integrates a mathematical formulation to objectively determine criteria weights, ensuring a balanced combination of subjective and data-driven inputs. A case study for a leading new energy vehicle manufacturer demonstrates the framework's effectiveness: among four evaluation criteria-Quality ([Formula: see text]), Cost ([Formula: see text]), Service level ([Formula: see text]), and Production capacity ([Formula: see text])-Cost ([Formula: see text]) received the highest weight (0.2789), and supplier [Formula: see text] emerged as the most sustainable choice. Comparative experiments against established MCDM techniques confirm the proposed approach's superior ranking stability and robustness. These results provide both a methodological advance for fuzzy decision-making research and a practical decision-support tool for industries pursuing environmentally responsible supply chain strategies.
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