建立铁路调度问题的开源库，统一标准便于算法对比与复现。
DISPLIB: a library of train dispatching problems
- 定义统一的铁路调度问题格式与数据规范
- 整合多个真实场景实例并公开可用
- 提供参考求解器，支持算法公平比较
基于优化的决策支持系统在铁路调度中具有巨大潜力，可通过自动重排和重调度列车来减少延误、提升效率。然而，现有研究多针对特定工业场景，代码与数据极少公开，导致可复现性差，且不同论文采用相近但不兼容的问题定义，难以评估算法性能差异。受MILP、SAT、TSP、VRP等成功社区启发，本文提出统一问题定义与文件格式——DISPLIB，涵盖列车重调度的核心特征。我们汇集了来自多个真实工业场景的问题实例，并公开发布。本文详细描述问题定义、实例集及参考求解器实现，使研究者无需工业合作即可开展研究，并推动求解器间的实证对比。所有资料可在https://displib.github.io获取。
原文摘要 · Abstract (English)
Optimization-based decision support systems have a significant potential to reduce delays, and thus improve efficiency on the railways, by automatically re-routing and re-scheduling trains after delays have occurred. The operations research community has dedicated a lot of effort to developing optimization algorithms for this problem, but each study is typically tightly connected with a specific industrial use case. Code and data are seldom shared publicly. This fact hinders reproducibility, and has led to a proliferation of papers describing algorithms for more or less compatible problem definitions, without any real opportunity for readers to assess their relative performance. Inspired by the successful communities around MILP, SAT, TSP, VRP, etc., we introduce a common problem definition and file format, DISPLIB, which captures all the main features of train re-routing and re-scheduling. We have gathered problem instances from multiple real-world use cases and made them openly available. In this paper, we describe the problem definition, the industrial instances, and a reference solver implementation. This allows any researcher or developer to work on the train dispatching problem without an industrial connection, and enables the research community to perform empirical comparisons between solvers. All materials are available online at https://displib.github.io.
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