The size of container ships and the number of containers being transshipped at container terminals have steadily increased over the years. Consequently, it is important to make efficient use of the hinterland capacity. A concept that is used to do this is synchromodal transportation, in which at the very last moment the mode of transportation for a container is decided. Unfortunately, some deep-sea terminals are rather congested and it is unknown by the time the transportation plan is made how many containers can be loaded to and unloaded from a barge. Motivated by this, we study an operational planning problem with uncertainty that is faced by an inland terminal in the port of Amsterdam as a two-stage stochastic problem with recourse. We solve this problem using sample average approximation (SAA) and a fast heuristic using constraints based on stochastic programming (SP). The SAA method gives near-optimal solutions for small instances. For larger instances, the SP-based method is shown to be a good alternative because it is much faster than the SAA method and produces solutions that are less than 1% from the SAA solutions.

多年来，集装箱船的大小和在集装箱码头转运的集装箱数量稳步增长。因此，重要的是要有效利用内陆的能力。用于实现此目的的概念是同步运输，在最后一刻，确定了集装箱的运输方式。不幸的是，一些深海码头相当拥挤，在制定运输计划时尚不知道可以将多少个集装箱装进驳船。因此，我们研究了具有不确定性的运营计划问题，该问题是阿姆斯特丹港内陆码头面临的具有追索权的两阶段随机问题。我们使用样本平均逼近（SAA）和使用基于随机规划（SP）的约束的快速试探法来解决此问题。SAA方法为小型实例提供了接近最佳的解决方案。对于较大的实例，基于SP的方法被证明是一个很好的选择，因为它比SAA方法快得多，并且生成的解决方案比SAA解决方案少1％。