Integrated optimization of vessel traffic organization and heterogeneous tugboat scheduling in a seaport with dual one-way channels

The joint optimization of vessel traffic organization and tugboat scheduling plays a critical role in improving the efficiency of port seaside operations. However, most existing studies are limited to single-channel environments or assume homogeneous tugboat fleets, whereas real-world ports are typically characterized by heterogeneous tugboat resources and, in some cases, complex multi-channel structures. To address this gap, this study investigates an integrated optimization problem combining vessel traffic organization with heterogeneous tugboat scheduling in a port with a dual one-way channel configuration. To capture the strong spatiotemporal coupling inherent in such operations, a bi-objective mixed-integer linear programming model is developed with the objectives of minimizing total weighted vessel waiting time and total tugboat fuel consumption. A tailored non-dominated sorting genetic algorithm incorporating an archive-guided adaptive multi-neighborhood search mechanism is proposed to efficiently solve the model. Computational experiments based on a northern Chinese seaport demonstrate that the proposed algorithm outperforms the CPLEX solver and several benchmark heuristic algorithms. The resulting Pareto solutions explicitly reveal the trade-off between vessel service efficiency and tugboat energy consumption, from which managerial implications are derived to support the formulation of coordinated scheduling strategies.