<p>This research develops a comprehensive inventory management framework for deteriorating items characterized by linear deterioration patterns and time-dependent demand, incorporating opportunity cost effects and backordering costs. Traditional Economic Order Quantity (EOQ) models, while mathematically elegant, often fail to capture the complex dynamics of perishable goods due to their assumptions of constant demand and negligible deterioration. The proposed model addresses these limitations through four key innovations: (1) linear deterioration where the rate increases temporally, (2) time-declining demand patterns reflecting market saturation, (3) opportunity costs of capital tied up in inventory, and (4) strategic backordering with associated penalty costs. The inventory dynamics are modeled using first-order linear differential equations solved analytically through the integrating factor method, yielding numerical approximation solutions for optimal order quantity, backorder levels, and cycle timing. Extensive numerical analysis demonstrates the model’s practical superiority, revealing a 5.4% reduction in operational costs in cost estimation compared to traditional EOQ approaches. Sensitivity analysis identifies demand parameters and interest rates as the most influential factors on total costs, providing managers with clear prioritization guidelines for improvement initiatives. The model offers significant theoretical contributions through its integrated analytical framework and practical value through actionable managerial insights for perishable goods inventory optimization across various industrial sectors.</p>