<p>This study presents an analytically optimized inventory management model that explicitly accounts for trade-credit policies, encompassing both permissible payment delays and interest on overdue balances. The framework simultaneously incorporates time-dependent demand, dynamic price discounts, and advertising influences to realistically capture purchasing behavior, while integrating learning effects that reflect evolving consumer responsiveness over time. A core aspect of the research is the exploration of how permissible delays in payment influence trade-credit policies and create financial leverage that benefits retail enterprises. Furthermore, the study analyzes the learning effect on inventory costs, accounting for improved forecasting accuracy, optimized order quantities, and streamlined supply chain operations. The model encompasses both perishable and non-perishable items, explicitly incorporating operational considerations such as partial backlogging, lost sales, disposal of deteriorated inventory, and fixed lead times. This comprehensive formulation enables a realistic representation of inventory dynamics and supports the analysis of cost-efficient replenishment and service strategies under varying demand and deterioration conditions. The primary objective of the proposed analytical framework is to derive optimal order quantities and cycle times that minimize the total system costs while adhering to trade-credit policies allowing for payment deferral. The theoretical findings are validated through numerical illustrations that emphasize critical insights into cost optimization. The numerical and graphical analyses confirm the convex nature of the nonlinear objective functions, reinforcing the model’s robustness. A sensitivity analysis further highlights the parametric influence on the total cost function, offering valuable insights for retail firms aiming to enhance inventory management strategies and achieve economic efficiency under trade-credit arrangements.</p>