Shuaiqi Wang

This study addresses the problems of vessel congestion and inefficient resource utilization caused by the independent scheduling of port berths and locks in river–sea intermodal transport. Moreover, this study explores the joint scheduling optimization problem for a single port and a single lock under the direct transshipment mode of seagoing and river vessels. First, considering the spatiotemporal coupling characteristics of the port–lock system, a mixed-integer linear programming model integrating seaside and riverside berth allocation, lock batch scheduling, and 2D layout constraints of the lock chambers is constructed. The objective is to minimize the time costs of seagoing vessels in a port, river vessels in a port, and river vessels passing through the locks. Second, a hierarchical iterative collaborative optimization algorithm is designed. The outer layer uses an iterative algorithm framework, while the inner layer utilizes a heuristic algorithm to address the lock scheduling problem. An adaptive large neighborhood search algorithm is used to address the berth scheduling problem. Finally, the model and algorithm are validated through numerical instances. Compared with the commercial solver CPLEX, the proposed algorithm HICOA achieves up to 81.45% lower costs in medium-to-large instances. Compared with independent scheduling, joint scheduling reduces the total vessel dwell time cost by up to 66.22%, demonstrating the significant value of port–lock collaboration. Furthermore, the arrival time window of river vessels and the ratio of the number of vessels to the number of berths have a significant influence on system performance.