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In order to alleviate the freight pressure of the terminal, improve the operational efficiency of the terminal, find out and cope with the adverse effects brought by various uncertain factors on berth and quay cranes allocation, a scenario-based stochastic programming model with uncertain arrival time and container handling volume is formulated. Based on the actual operations of the terminal, the relevant numerical experiments were designed, and they were solved by CPLEX. The experimental results showed that the proposed integrated optimization model is valid in dealing with uncertainties. Meanwhile, it is found that the greater the arrival time fluctuation or the container volume fluctuation, the greater the impact on the plan. And the impact of time fluctuation is greater than that of container volume fluctuation. The relevant study results have practical significance in guiding the integrated optimization of berth and quay cranes allocation under uncertainty.

usc Refereed/Peer-reviewed The relationship between container location dispersion for a single loading and the efficiency of quay cranes (QCs) was investigated. For this purpose, a discrete-event-based simulation model was developed to capture the container handling process at a transshipment container terminal. A series of experiments were conducted to illustrate the effects of container location dispersion on the long-term performance of QCs and container allocation. These experiments showed that the container location dispersion has a significant effect on the distribution of loading containers. An optimal choice of container location dispersions can improve the efficiency of the QC and help to manage uncertainty at a lower cost. It is suggested that yard managers consider the workload of each berth when deciding on the location dispersion for a loading service. In addition, it was found that optimal container allocation dispersion reduces the congestion caused by time window conflicts and insufficient available equipment.