Joint optimization of vessel scheduling and tugboat allocation in seaports with one-way navigation channels

With the continuous growth of port traffic volumes, limited navigation channel capacity and tugboat resources have emerged as major bottlenecks to port service efficiency, particularly in ports with one-way channel configurations, where vessel congestion is more pronounced. To address this challenge, this study investigates the joint optimization of vessel scheduling and tugboat allocation in a port with a one-way navigation channel and develops an optimization model to minimize the total waiting time of vessel movements. An improved genetic algorithm with local search (IGA-LS) is proposed to solve the model efficiently. Computational experiments based on data from a northern Chinese seaport demonstrate that the proposed IGA-LS algorithm outperforms several benchmark methods. Compared with the traditional first-come-first-served scheduling rule, the proposed joint scheduling framework reduces the total vessel movement waiting time by an average of 28.31%, with more pronounced improvements observed in larger-scale instances. These results indicate that the proposed model and algorithm can provide effective decision support for port authorities in formulating vessel scheduling and tugboat resource allocation plans.