Rescheduling optimization of ships and berths at hub ports during short-term channel closures

To flexibly respond to the impact of short-term closure events at hub ports, the coordinated optimization of ship scheduling and berth allocation at container hub ports was investigated. By focusing on a container hub port with a one-way channel, uncertainty events within the channel that caused partial closures during certain periods were primarily considered. The impact of variations in the expected arrival information of feeder and mainline ships on ship scheduling and berth allocation was taken into account, and a rescheduling decision mechanism was proposed to deal with different scenarios. Both the time constraints imposed by the arrival and departure schedules of the one-way channel and the time required for feeder-to-mainline transshipment operations were considered, and a mathematical model that minimized the sum of the total service cost of the ships and the penalty costs for uncompleted transshipment of feeder ships was constructed. Next, an improved genetic algorithm incorporating the variable neighborhood search (VNS) approach was designed based on the model characteristics. In consideration of the reordering of ship arrival and departure sequences and local adjustments in the actual scheduling process, Cross, 2-opt, and Or-opt operators were designed. To avoid local optima, the operators were randomly selected for neighborhood search based on the ideas of VNS to replace the traditional crossover and mutation operations in genetic algorithms. To enhance population diversity and prevent premature convergence in the search process, interference rules were also incorporated into the algorithm. Finally, multiple sets of ship scheduling case studies of different scales were conducted. The results show that compared to the first-come and first-served strategy and the scheme that only considers berth allocation, the optimal ship and berth resheduling plans obtained by the model and algorithm in this study can reduce the total cost by 28.56% and 11.78%, respectively. The solving efficiency of the algorithm is superior to that of the harmony search algorithm and the immune genetic algorithm. Both the duration and timing of closures affect the total cost, with the timing having a more significant impact. These findings provide valuable decision-making support for port operations.