This paper presents a novel mathematical formulation in railway crew scheduling, considering real challenges most European passenger railway companies face like roundtrip policy for crew members joining from different cities and stricter working time standards. To solve the problem in large scales of data (consistent with the real case size of the planning problems solved by rail transport companies), a solution algorithm is proposed. The algorithm includes two steps: I. Duty generation: pre-calculations to obtain all duties meeting the related constraints; II. Duty assignment: running the optimization model to select an optimal set of duties while satisfying other constraints. To investigate the algorithm’s efficiency, numerical test instances and a real case study have been employed. In addition, the savings that an implementation of the proposed approach allows to achieve instead of the manually prepared plans still applied in a lot of transportation companies are demonstrated. Results show that the proposed model and algorithm lead to considerable improvement compared to the original planning.

考虑到大多数欧洲客运铁路公司面临的实际挑战，例如针对来自不同城市的机组人员的往返政策和更严格的工作时间标准，本文提出了一种新颖的数学公式，用于铁路机组人员调度。为了解决数据量大的问题（与铁路运输公司解决的规划问题的实际情况相符），提出了一种求解算法。该算法包括两个步骤：I.职责生成：预先计算以获得满足相关约束的所有职责；二。职责分配：在满足其他约束的同时，运行优化模型以选择最佳职责集。为了研究该算法的效率，采用了数值测试实例和实际案例研究。此外，证明了所提出的方法的实现可以实现的节省，而不是仍然适用于许多运输公司的手动准备的计划。结果表明，与原计划相比，所提出的模型和算法带来了很大的改进。