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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.
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