The paper presents: the terminal’s infrastructure, the loading’s plans, the equipment’s details, the operational data onboard, the systemic analysis of the terminal. In order to highlight the operational optimization in the cargo terminal, operating scenarios are proposed, to which simulation models are attached. Enter parameters such as towing units, return / load / unload speed, the distance between parallel and opposite parking rows and the load pick-up time, using working diagrams. It simulates the operability in the terminal. In the analyzed terminal, the expected size of the ship is not found in the equations attached to a simulation model, because the degree of berth occupancy is actually related to the number of access points, where a frame can be placed and not the length available berth. The terminal usually operates by scheduling ships in advance and therefore arrival times are usually planned in advance and follow a strict schedule. The simulation results (performance indicators) lead to the estimation of the values for the optimal quay time, in relation to the number of units for loading in the proposed scenarios. It takes into account whether the arrival pattern is random or scheduled and the time of service provided by the terminal. Also, the different types of goods and their distribution on the quay are identified and taken into account. A methodology for assessing the level of service provided by the terminal under certain operational constraints is also provided, in part, as a by-product of the methodology.

Container terminals are the actual backbone of break bulk cargo transport around the world. Pressure by supply chains, coupled with the rapid growth in cargo amounts, result in an ever-increasing demand for productivity optimizations in this highly competitive market. Within short time windows, many cargo handling processes occur in parallel, and operational decisions should take into account both time efficiency and equipment utilization. Waterside operations consist in handling of containers by quay cranes, land based guided vehicles and yard cranes. The container relocation problem that minimizes the number of moves needed to retrieve all containers, while respecting a given order, is studied in parallel with the quay cranes scheduling to find an optimal sequence of crane operations that perform the required container movements. Starting with real data from Constanta Container Terminal, and studying the statistical relevance between operational indicators and applied inverse statistics as a pertinent tool for waiting time expectancy. In the paper is proposed a simulation based-optimization process viewing the dynamics of the Container Terminal as a complex system, because during operation, many sources of disturbance and uncertainty exist. Possible designs are investigated in the framework of Bayesian optimization and Simulated Annealing of the proposed time convergence algorithms. The research in the paper is based on real data from Constanta Container Terminal, and studied the statistical relevance between operational indicators and applied inverse statistics as a pertinent tool for waiting time expectancy.