Modeling Port Congestion Using Queueing Theory: The Case of the Autonomous Port of Conakry

This article highlights the relevance of queuing theory as a decision-making tool for solving congestion problems in Guinean ports, particularly of the Autonomous Port of Conakry (APC). Port congestion, which often causes delays and additional logistics costs, is a major obstacle to economic development. Using an analytical approach and numerical simulation, the study proposes a realistic model of the operation of the APC container terminal based on the GI/GI/c general queuing model, adapted to complex systems where the distributions of arrivals and services are not necessarily exponential. The Statistical tests performed on empirical data from the year 2023 revealed that ship inter-arrival times follow a Weibull distribution, while service times are well described by a Gamma distribution. Integrating these distributions into the GI/GI/c framework enabled realistic simulation of the port system’s behavior. The simulation results show an average waiting time of about 1.4 days, a berth occupancy rate of 43%, and a high probability that the system is empty, indicating good operational fluidity. The average observed service rate, estimated at 0.033 ships/hour, demonstrates the port’s ability to efficiently handle vessels without generating congestion. These performances confirm the positioning of the Autonomous Por3t of Conakry, through its container terminal, among the most efficient in West Africa in 2023. The methodological approach developed in this paper, combining probabilistic modeling and simulation, can be extended to other ports in the region for comparative analysis, to support strategic planning of port infrastructure, and to guide decision-making regarding investment and capacity optimization.