The optimization of berthing operations has a significant impact on the overall performance of port infrastructures, providing various benefits such as the reduction of operational time, minimization of fuel consumption, and optimization of resource planning, among others. Berthing planning depends on the arrival of vessels at the port, which introduces a high degree of uncertainty due to its dependency on external factors. This paper presents a new decision support system aimed at managing the stay of vessels in ports. This software provides real-time tracking of vessels’ positions and identifies the efficient berthing position for each incoming vessel. To determine the berthing positions, the software solves the Berth Allocation Problem (BAP), incorporating container movement costs and real-time vessel position data from the Automatic Identification System (AIS) to predict their arrival at ports. To solve this problem, the software integrates a Greedy Randomized Adaptive Search Procedure (GRASP). GRASP dynamically allocates berths, minimizing container movement expenses and orchestrating efficient vessel sequencing within port infrastructures. Results demonstrate the software’s effectiveness in proactive planning, resource allocation, and congestion mitigation.