Applying λ -Statistical Convergence in Fuzzy Paranormed Spaces to Supply Chain Inventory Management Under Demand Shocks ( D S )

Hasan Öğünmez and Muhammed Recai Türkmen ()
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Hasan Öğünmez: Department of Mathematics, Faculty of Science and Literature, Afyon Kocatepe University, Afyonkarahisar 03200, Turkey
Muhammed Recai Türkmen: Department of Mathematics and Science Education, Faculty of Education, Afyon Kocatepe University, Afyonkarahisar 03200, Turkey

Mathematics, 2025, vol. 13, issue 12, 1-21

Abstract: This paper introduces and analyzes the concept of λ -statistical convergence in fuzzy paranormed spaces, demonstrating its relevance to supply chain inventory management under demand shocks. We establish key relationships between generalized convergence methods and fuzzy convex analysis, showing how these results extend classical summability theory to uncertain demand environments. By exploring λ -statistical Cauchy sequences and ( V , λ ) -summability in fuzzy paranormed spaces, we provide new insights applicable to adaptive inventory optimization and decision-making in supply chains. Our findings bridge theoretical aspects of fuzzy convexity with practical convergence tools, advancing the robust modeling of demand uncertainty.

Keywords: fuzzy paranormed spaces; λ-statistical convergence; supply chain modelling; inventory management; demand forecasting (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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