Vessel voyage schedule planning for maritime ore transportation

This paper introduces a vessel voyage schedule planning problem for maritime ore transportation arising from a real-world project in Boffa, Guinea. In this problem, delay of vessel arrivals at the loading port often occurs which interrupts the ore loading operation and further impacts the yearly throughput of ore transportation, which dues to variable weather conditions at sea and changing loading/discharging time at ports. Thus, factors regarding the uncertainty of vessel voyages must be considered in order to ensure continuous vessel arrivals and uninterrupted loading operations at the original port, leading to an increase in the overall productivity of the project. And at the same time, since every voyage entails an increase in costs, cost control is necessary to be accounted for, so there is also a need to consider minimizing operating costs. In this study, to address the uncertainty in voyage duration, a chance-constrained model is introduced to obtain sailing schedules as well as the associated costs within a given confidence level. And then, for the multi-objective requirements, we develop a multi-objective planning model and the actual system operating capacity limitation constraints are considered. After that, considering that the multi-objective model cannot be solved by the solver directly, the weighting method is introduced. Afterwards, since the direct solving of the model is rather time-consuming, valid cuts are designed to accelerate it. Finally, considering that the Pareto solutions of multi-objective problems are numerous, a nondominated sorting genetic algorithm II (NSGA-II) is launched with the aim of providing more solutions to the manager in a shorter time. In terms of experiments, each of the aforementioned issues and proposed remedies are verified. The results confirm the effectiveness of the valid cuts and NSGA-II, and demonstrate that the obtained vessel voyage schedule is more robust and outperforms manual decisions.