考虑配载计划的多式联运集装箱堆存箱位分配研究

    Space Allocation for Intermodal Container Stacking Considering Stowing Planning

    • 摘要: 集装箱多式联运港口作为联运网络的核心节点,其作业效率与整个联运网络的通过效率直接相关,而堆场作业效率对港口整体效率保证尤为重要。港口实际作业中,基于船舶配载计划对堆场待装船集装箱进行合理的箱位分配,可以有效提高堆场作业效率。在集装箱多式联运背景下,考虑船舶配载计划,以公路、铁路、水路集港的待装船集装箱为对象,结合场桥作业研究堆场集装箱的箱位分配问题。为保证堆场整体作业效率,建立集装箱堆场翻箱量最小和场桥作业时间最短的两阶段数学模型,并运用改进人工蜂群算法进行求解。为避免两阶段求解对全局最优影响,通过信息素与灵敏度协同来平衡两阶段最优解得到最优方案。算例研究表明:改进人工蜂群算法求解得到的堆场翻箱量和场桥作业时间均优于人工蜂群算法和遗传算法;随着算例规模的增大,改进人工蜂群算法的优势更加凸显,求解质量和效率均表现最好。以上结果论证了所构建模型与算法的有效性,对于港口实际制定堆场箱位分配计划具有一定的参考意义。

       

      Abstract: As the core node of an intermodal container transport network, the operation efficiency of a container intermodal port is directly related to the overall throughput of the network, with the storage yard operations being particularly important to ensure port efficiency. In actual port operations, reasonable space allocation of containers waiting for loading based on the ship stowage plan can effectively improve the yard efficiency. Under the background of container intermodal transportation, the space allocation of containers in storage yard is studied by considering ship stowing planning, where containers arriving at the port via road, railway and waterway, combining with yard bridge operations. In order to ensure the overall operation yard efficiency, a two-stage mathematical model is proposed, with the objective of minimizing container reshuffling and bridge operation time. An artificial bee colony algorithm is improved to solve the problem. In order to mitigate the influence of the two-stage solution on the global optimum, the optimal scheme is obtained by the coordination of pheromone and sensitivity to balance the optimal solutions of both stages. Results show that the improved artificial bee colony algorithm outperforms the general artificial bee colony algorithm and genetic algorithm in reducing container reshuffling and bridge operation time. With the increase of the problem scale, the advantages of the improved artificial bee colony algorithm are more prominent in both solution quality and computational efficiency. The results above verify the effectiveness of the proposed model and algorithm, providing a certain reference significance for the actual development of space allocation plans by storage yard.

       

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