<![CDATA[This study aims to develop a novel Economic Production Quantity (EPQ) model that integrates important sustainability and operational factors reorders, rework, imperfect quality, emission taxes, and variable electricity tariffs- by minimizing the total inventory cost while considering environmental and energy-related constraints. The model is formulated as an Integer Non-Linear Programming (INLP) problem, with two main decision variables: the total number of products produced in a cycle (y) and the maximum allowable reorder level (w). To solve this complex optimization problem, the Genetic Algorithm (GA) is used for its efficiency in handling non-linear and combinatorial problems. In addition, a sensitivity analysis is performed to assess the impact of various parameters on the total cost. Numerical experiments show that increasing emission taxes, electricity tariffs, and installation costs significantly increase the total inventory and production costs. In particular, higher emission taxes and electricity tariffs amplify the financial burden on manufacturers, underscoring the economic implications of environmental regulations and energy use. These findings emphasize integrating operational and ecological considerations into production planning. This study contributes to the field by offering a comprehensive framework that supports sustainable manufacturing practices through cost-effective inventory management. The proposed EPQ model enables manufacturers to balance economic performance and ecological responsibility, aligning operational strategies with sustainability goals and regulatory compliance.]]>
