<![CDATA[Distribution is an important aspect that affects the operational efficiency of a company, especially in terms of goods delivery. This study aims to develop an optimization model for LPG gas distribution routes using Excel Solver based on geographic coordinate conversion. In this study, the method used includes converting geographic coordinates from decimal to Degree-Minute-Second (DMS) format, followed by conversion to kilometers to form a more accurate distance matrix. The optimization model was built using the Capacitated Vehicle Routing Problem (CVRP) approach, which takes into account vehicle capacity constraints (a maximum of 560 cylinders per truck) and the limited number of available fleets, which is only one truck. The results show that coordinate conversion produces high accuracy in calculating distances between distribution locations. By using Excel Solver, the optimization solution successfully minimizes the total distance traveled compared to the conventional route, where distribution is carried out more evenly to 57 scattered LPG base locations. The addition of Solver Parameters Evolutionary and All Different constraints proved effective in avoiding duplication of visits and producing optimal distribution routes. This solution not only improves distribution time and cost efficiency, but also improves service to customers by reducing delivery delays. The success of this optimization model is expected to be implemented by other distribution companies to improve their operational performance. This study also highlights the importance of selecting the right software to aid the distribution optimization process. Excel Solver, despite its simplicity, proved highly effective in solving complex distribution routing problems, especially when combined with coordinate conversion techniques that yield more accurate distances. Furthermore, the application of the CVRP method enabled more efficient decision-making in determining distribution routes, taking into account vehicle capacity and fleet limitations.]]>
