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Personnel Scheduling on Railway Yards

机译:在铁路院子里调度人员

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摘要

In this paper we consider the integration of the personnel scheduling into planning railway yards. This involves an extension of the Train Unit Shunting Problem, in which a conflict-free schedule of all activities at the yard has to be constructed. As the yards often consist of several kilometers of railway track, the main challenge in finding efficient staff schedules arises from the potentially large walking distances between activities. We present two efficient heuristics for staff assignment. These methods are integrated into a local search framework to find feasible solutions to the Train Unit Shunting Problem with staff requirements. To the best of our knowledge, this is the first algorithm to solve the complete version of this problem. Additionally, we propose a dynamic programming method to assign staff members as passengers to train movements to reduce their walking time. Furthermore, we describe several ILP-based approaches to find a feasible solution of the staff assignment problem with maximum robustness, which solution we use to evaluate the quality of the solutions produced by the heuristics. On a set of 300 instances of the train unit shunting problem with staff scheduling on a real-world railway yard, the best-performing heuristic integrated into the local search approach solves 97% of the instances within three minutes on average.
机译:在本文中,我们考虑将人员调度整合到规划铁路码。这涉及列车单位分流问题的延伸,其中必须建设院子里所有活动的无冲突计划。随着院子通常由几公里的铁路轨道组成,寻找高效员工计划中的主要挑战是出现在活动之间的潜在大型步行距离中。我们为员工分配提供了两个有效的启发式。这些方法集成到本地搜索框架中,以找到与员工要求的列车单位分流问题找到可行的解决方案。据我们所知,这是解决这个问题完整版本的第一个算法。此外,我们提出了一种动态的编程方法,将工作人员分配为乘客,以培训运动来减少步行时间。此外,我们描述了几种基于ILP的方法,以找到具有最大稳健性的员工分配问题的可行解决方案,我们使用的解决方案来评估由启发式产生的解决方案的质量。在一组火车单位分流问题上与现实世界铁路围场的员工调度的一套300个实例,集成到本地搜索方法的最佳性启发式符合在三分钟内的97%的实例。

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