69A double parametric fuzzy optimization method for solving LPP with symmetric trapezoidal uncertainty

This paper presents a double parametric form for symmetric trapezoidal FNs, a novel technique for addressing fuzzy linear programming (FLP) issues among uncertainty. Conventional approaches frequently reduce fuzzy limits to precise equivalents, which may result in the loss of vital information essential for decision-making in practical scenarios. The proposed technique preserves and regulates this complexity through the use of a dual-parametric model that directly addresses symmetric trapezoidal FNs. This facilitates precise adjustment of uncertainty levels via parameters α and β , offering decision-makers adaptable solutions under diverse limitations. The suggested method has been evaluated on representative FLP situations, demonstrating enhanced accuracy and adaptability, but it requires greater computer resources than conventional crisp-based methods. The proposed method enhances the application of FLP models in complex domains, such as logistics, finance, and operations, by preserving the integrity of fuzzy data, where uncertainty is inherent.