Optimization of Integrated Tugboat–Berth–Quay Crane Scheduling in Container Ports Considering Uncertainty in Vessel Arrival Times and Berthing Preferences

Abstract

Influenced by the dynamics of supply and demand, the demand for maritime transport has been increasing annually, putting significant pressure on container ports. To alleviate this pressure, a new mixed-integer programming model for the integrated scheduling of tugboats, berths, and quay cranes has been established. This model considers the uncertainties in vessel arrival times, vessel berthing preferences, time-varying quay crane availability, and the constraint that quay cranes cannot cross each other. The objective is to minimize the total costs including fuel consumption during port stays, delays and waiting times for berthing and departure, berthing deviation costs, tugboat assistance costs, and quay crane handling costs. To obtain high-quality solutions, an adaptive large neighborhood search (ALNS) algorithm was employed to solve the model. The algorithm incorporated five destruction operators and five repair operators that were specifically designed to enhance the solution accuracy and efficiency for the integrated scheduling problem. Several case studies of varying scales, based on a port in China, were used to validate the effectiveness of the proposed model and algorithm. The experimental results demonstrate the model’s validity and show that the ALNS algorithm designed for the integrated scheduling problem outperformed CPLEX and other algorithms in terms of the accuracy and efficiency. Finally, a sensitivity analysis of the key parameters provides recommendations for the integrated scheduling of tugboats, berths, and quay cranes, offering valuable insights for port operations.

Keywords

• waterway transportation
• integrated tugboat–berth–quay crane scheduling
• mixed-integer linear programming model
• adaptive large neighborhood search algorithm
• uncertainty in vessel arrival times
• berthing preferences