<p>Inventory management of perishable goods presents significant challenges due to time-dependent deterioration and market-driven demand variability. Many products retain quality for a finite period before deterioration accelerates, necessitating realistic modelling of non-instantaneous decay. This study develops an economic order quantity (EOQ) model for non-instantaneous deteriorating items in which demand depends on selling price, and deterioration follows a two-parameter Weibull distribution. To incorporate parameter uncertainty arising from fluctuating market conditions, six key inventory parameters are represented as triangular fuzzy numbers.The fuzzy total cost function is defuzzified using three approaches: Graded Mean Integration Representation (GMIR), Signed Distance, and Centroid methods. The optimal cycle length is obtained by minimising total cost per unit time. Numerical analysis demonstrates that incorporating fuzzy parameters reduces total cost compared to the crisp model. Among the defuzzification techniques, the Centroid method yields the minimum optimal cost, followed by the Signed Distance method and GMIR. Sensitivity analysis confirms the robustness of the model with respect to demand, deterioration, and shelf-life parameters. The proposed framework provides a decision-support tool for managing perishable inventory systems under uncertainty.</p>