Collaborative Optimization of Container Liner Slot Allocation and Empty Container Repositioning Within Port Clusters

The imbalance between supply and demand for slot resources and empty containers has led to resource waste and excessive operating costs for liner companies. Moreover, intense competition among ports has made both container ship slots and port equipment resource allocation inefficient. To address these challenges, this paper aims to solve the collaborative optimization problem of slot allocation and empty container repositioning within port clusters concerning inventory control. A cooperative possession strategy and a hybrid (T, s) inventory control policy are incorporated in this paper. A novel mixed-integer programming model is proposed, enabling us to simultaneously track slot allocation, empty container repositioning, empty container leasing, and slot renting. To solve the model, a new branch-and-bound algorithm based on Lagrangian relaxation and the ascendancy principle (BBLRAP) is developed. Numerical experiments are conducted to demonstrate the effectiveness of the proposed model and algorithm. The results show that the new collaborative optimization method, incorporating the cooperative possession strategy and (T, s) inventory policy, can increase liner company revenues by expanding market share, reducing costs, and improving the utilization of slot resources, ultimately achieving a win–win outcome for both liner companies and their partners. Compared to state-of-the-art studies, the following paper makes new contributions to proposing a cooperative possession strategy within port clusters for the first time. This paper ensures that liner companies and partners achieve a win–win situation in the cooperative game, expanding market shares and improving customer satisfaction.