Ship scheduling problem based on channel-lock coordination in flood season

Channels and locks are crucial resources for ships of inland waterways. This paper addresses the ship scheduling problem based on channel-lock coordination, where ships entering the channel are affected by water discharge during flood season. A ship scheduling optimization model is formulated to minimize the total waiting time of ships at the anchorage. The model takes into account the decision-making of the departure time of ships, the change of water discharge in different scenarios, and the coordinated allocation of channels and locks. A dynamic multi-population particle swarm optimization algorithm with recombined learning and hybrid mutation (DMPSO-RH) is proposed to solve the model of ship scheduling. Numerical experiments conducted for the Three Gorges Dam (TGD) demonstrate that the DMPSO-RH can obtain nearly optimal solutions for practical large-sized ship scheduling problems within a reasonable time. By optimizing the departure time and sequence of ships, the scheduling scheme generated by the DMPSO-RH can effectively match the channel operation time and the lockage starting time, which helps to enhance the coordination of channels and locks at the TGD in different scenarios. Due to these improvements, the total waiting time of ships in the two scenarios is reduced by 29.08% and 28.59%, respectively, and the carbon emissions of ships are reduced accordingly. This approach can avoid navigation risks and improve the efficiency of ship scheduling in flood season. Moreover, the result of this study is very useful to reduce the waiting time and improve the environmental pollution of ships at the TGD.