<![CDATA[Efficient transportation management plays a vital role in minimizing operational costs in the tobacco manufacturing industry. This study presents the application of Integer Programming using Excel Solver to optimize distribution logistics and reduce transportation expenses in a cigarette factory. The research employs a quantitative descriptive approach using simulated data representing production capacities and regional demand. A linear programming model is constructed to minimize total transportation costs while considering constraints such as factory capacity, regional demand, and non-negativity of shipment volumes. Excel Solver, as an accessible and widely adopted optimization tool, is utilized to determine the optimal allocation of product deliveries from factories to various distribution zones. The results indicate that Solver provides a cost-effective and practical solution for identifying optimal transport routes, reducing overall distribution costs, and improving operational efficiency. Furthermore, sensitivity analysis reveals the robustness of the model in responding to changes in cost parameters and capacity constraints. The study highlights the strategic potential of spreadsheet-based decision support systems in enhancing supply chain efficiency within the tobacco industry and similar manufacturing sectors..]]>
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