This study successfully applied Dijkstra’s Algorithm to optimize waste collection routes in Kuppiyawatha East, Colombo District, Sri Lanka, demonstrating its effectiveness in minimizing travel distances and improving operational efficiency. The algorithm computed an optimized path covering all collection points with a total travel distance of 3,450 meters, following the sequence of nodes representing waste collection points: [1, 17, 10, 4, 9, 8, 20, 6, 12, 15, 2, 19, 13, 18, 21, 14, 7, 11, 5, 16, 3, 22]. This optimized route significantly reduced unnecessary detours compared to unstructured routing methods. The results confirm that route optimization can enhance waste collection processes by lowering fuel consumption, reducing operational costs, and streamlining municipal waste transportation. Despite the success of the optimized model, certain limitations were identified. The study lacked real depot route data, preventing direct comparison with existing municipal collection practices. Additionally, the model was based solely on distance minimization, without incorporating factors such as vehicle capacity constraints, real-time traffic conditions, or operational costs. Addressing these limitations in future research by integrating cost-based route optimization, real-time waste tracking, and adaptive routing algorithms would further enhance the model’s practical applicability. Nevertheless, this research provides a strong foundation for waste transportation optimization in Sri Lanka, demonstrating how graph-based algorithms can improve municipal waste collection systems. The findings emphasize the need for data-driven approaches in urban waste management, offering a roadmap for developing smarter, more efficient, and environmentally sustainable waste collection strategies in the country.