Linear programming is a mathematical approach used to increase the revenue of a grocery store through the analysis of the most optimal combination of products. This study aims to identify the main constraints faced by grocery stores, such as limited capital, storage capacity, and consumer demand. Furthermore, an optimization model based on linear programming was developed to overcome these constraints. This research applies Simplex and Branch and Bound method to find the best solution. The results showed that the application of linear programming model is able to help stores determine the number of products that need to be sold efficiently to maximize revenue. This optimization process also allows for more optimal utilization of existing resources, thus supporting more effective and data-driven decision making. This study provides an important contribution in the management of grocery stores, especially in improving operational efficiency and revenue, and can be a reference for other small business actors.