Minimizing the risk of seaport operations efficiency reduction affected by vessel arrival delay

In seaport industries, vessel arrival delay is inevitable because of numerous factors, e.g. weather, delay due to the previous stop, etc. The period of delay can be as short at 15 min of as long as a few days. This causes disruption to the planned sea operation operations, and more importantly, to the resources utilization. In traditional berth allocation and quay crane assignment problems (BA-QCA), the risk of vessel arrival delay has not been considered. Accordingly, the purpose of this paper is to employ a proactive planning approach by taking into consideration the vessel arrival delay into the optimization of BA-QCA problems.

In the existing BA-QCA problems, vessel arrival time is usually deterministic. In order to capture the uncertainties of arrival delay, this paper models the arrival time as a probability distribution function. Moreover, this paper proposes to model the delay risk by using the period between the expected arrival time and the expected waiting time of a vessel. Lastly, the authors propose a new modified genetic algorithm and a new quay crane assignment heuristic to maximize the schedule reliability of BA-QCA.

A number of numerical experiments are conducted. First of all, the optimization quality of the proposed algorithm is compared with the traditional genetic algorithm for verifying the correctness of the optimization approach. Then, the impact of vessel arrival delay is tested in different scenarios. The results demonstrate that the impact of vessel arrival delay can be minimized, especially in the situations of high vessel to potential berth ratio.

The proposed vessel arrival modeling approach and the BA and QCA approach can increase the operations efficiency of seaports. These approaches can increase the resource utilization by reducing the effect of vessel arrival delay. In other words, this can improve the throughput of seaport terminals.

This paper proposes to minimize the delay risk based on the conditional probability of the vessel completion time based on the previous vessel at the assigned berth. This modeling approach is new in literature.