Abstract
This paper delves into the academic significance of addressing both the Traveling Sales-man Problem (TSP) and the Vehicle Routing Problem (VRP). It conducts a comparative analysis between a source-driven method and the Nearest Neighbor algorithm, both fall-ing under the category of greedy algorithms, in the context of TSP resolution. Focused on a national-scale transportation network with five logistic centers and sixty-two retail stores, the study illuminates the computational challenges in optimizing wide-area logis-tics. Implementing state-of-the-art technologies, including Docker for containerization and PHP Symfony with Doctrine ORM for backend development, the study introduces a highly scalable application. The system utilizes a MySQL database to store actual road distances between nodes, enabling the determination of the minimum-cost route from lo-gistic centers to multiple stores and back, emphasizing the utilization of real road distanc-es. This research offers valuable insights into addressing real-world computational chal-lenges in Logistics through a practical and scalable application. Emphasizing the scalabil-ity and processing power of the implemented solution, along with the utilization of cut-ting-edge tools and frameworks widely adopted in the IT industry, adds depth to its technological significance.