<![CDATA[The main issue faced is how to minimize delays and avoid penalties in fuel distribution, which is characterized by dynamic conditions. This study aims to optimize the distribution routes of fuel oil (BBM) to gas stations (SPBU) using a genetic algorithm at the Tasikmalaya Fuel Terminal. The research adopts a descriptive quantitative approach. By applying the Capacitated Vehicle Routing Problem with Time Windows (CVRPTW) method, the genetic algorithm is expected to generate optimal solutions in terms of distance and time variables. The study focuses on several constraint variables, including operational costs, vehicle carrying capacity, vehicle utilization, and potential penalties. The collected data covers fuel demand, tank truck capacity, distances between the Tasikmalaya Fuel Terminal and SPBU, travel time, operational costs, loading and unloading times, tank truck specifications, and tank truck usage within one delivery period. The results indicate that implementing this model can reduce the risk of delivery delays. In the initial data, the tank truck with license plate Z9357TB was scheduled to deliver fuel to three different SPBU. At the final destination, however, a delay occurred: the truck arrived at SPBU 34.46.310 17.5 minutes late. After route optimization using the genetic algorithm by selecting the shortest route as the initial sequence for visiting SPBU, the delay was minimized to 0.0 minutes, meaning the final destination SPBU no longer experienced delays. In addition, this study provides recommendations to the company regarding the implementation of the route optimization model and identifies opportunities for further development to enhance the model’s effectiveness.]]>
