In the last decades the intermodal transportation of containers has become a key component of the entire international trade system, as it allows safe and efficient intercontinental door-to-door movement of freight by combining land and sea transportation services. Intermodal railway terminals are special components of these systems that allow container traffic to be consolidated from different sources and to be transported by train over long distances. This paper addresses a practical problem faced by a major North American railway. On a daily basis, terminal operators must make several decisions such as how inbound trains are split into sequences of railcars, on which tracks these railcars are parked for loading and off-loading operations, and how the railcars are assigned to outbound blocks so as to fulfill the demand of each block. We introduce an approach that incorporates all these decisions to obtain improved solutions. In a first step, a mixed integer linear programming (MILP) model is used to create a set of patterns that specify how each inbound train is split and how the railcars are assigned to the blocks. Then, in a second step, another MILP formulation decides which patterns to use and where to park the railcars. Tests on generated benchmark instances based on realistic data from the railway indicate that our approach is able to generate good quality solutions for all instances and can be used by the company to assist decision makers in generating less costly and more efficient plans.

在过去的几十年中，集装箱多式联运已成为整个国际贸易体系的关键组成部分，因为它结合了陆路和海上运输服务，可以安全，高效地进行洲际门到门的货运。多式联运铁路枢纽是这些系统的特殊组成部分，可从不同来源整合集装箱运输，并通过火车长距离运输。本文解决了北美主要铁路面临的实际问题。终端运营商每天必须做出几项决定，例如如何将入站火车拆分为有轨电车序列，将这些有轨电车停放在轨道上以进行装卸操作，如何将有轨电车分配给出站区块以便满足每个街区的需求。我们引入一种结合所有这些决策以获得改进解决方案的方法。第一步，使用混合整数线性规划（MILP）模型来创建一组模式，这些模式指定如何拆分每个入站列车以及如何将轨道车分配给这些块。然后，在第二步中，另一种MILP公式决定使用哪种模式以及在哪里停放轨道车。根据来自铁路的实际数据对生成的基准实例进行的测试表明，我们的方法能够为所有实例生成高质量的解决方案，并且可被公司用来协助决策者生成成本更低，效率更高的计划。混合整数线性规划（MILP）模型用于创建一组模式，这些模式指定如何拆分每个入站火车以及如何将轨道车分配给这些块。然后，在第二步中，另一种MILP公式决定使用哪种模式以及在哪里停放轨道车。根据来自铁路的实际数据对生成的基准实例进行的测试表明，我们的方法能够为所有实例生成高质量的解决方案，并且可被公司用来协助决策者生成成本更低，效率更高的计划。混合整数线性规划（MILP）模型用于创建一组模式，这些模式指定如何拆分每个入站火车以及如何将轨道车分配给这些块。然后，在第二步中，另一种MILP公式决定使用哪种模式以及在哪里停放轨道车。根据来自铁路的实际数据对生成的基准实例进行的测试表明，我们的方法能够为所有实例生成高质量的解决方案，并且可被公司用来协助决策者生成成本更低，效率更高的计划。