Joint optimization of ship traffic organization and berth allocation in a seaport with one-way channel

Numerous seaports operate with one-way navigation channels, requiring ships to queue for both entry and exit, which frequently results in substantial delays. With increasing volume of arriving vessels, the waiting times for dispatch rise significantly, especially in multi-harbor basins with intricate traffic conditions. To address this challenge, this study introduces a mixed-integer linear programming model for the integrated optimization of ship traffic organization and berth allocation in ports with one-way navigation channels and multi-harbor basins. The objective of this model is to minimize the weighted sum of the waiting times for all vessels. A hybrid genetic algorithm (HGA) is developed to solve the model efficiently within a reasonable time frame. Computational experiments conducted for a northern Chinese seaport demonstrate that: (i) the proposed HGA outperforms both the CPLEX solver and several heuristic algorithms, solving all problem instances within 1 min; and (ii) the joint scheduling model reduces waiting times by 32.18% compared with the traditional first-come-first-served rule. This research offers practical insights for port managers, aiming to enhance ship scheduling, reduce waiting times, and to improve the overall service quality of seaports.