A fast recovery from disruptions is of vital importance for the reliability of transit systems. This study presents a new attempt to tackle the transit disruption mitigation problem in a comprehensive and hierarchical way. A network level strategy selection optimization model is formulated as a joint routing and resource allocation (nJRRA) problem. By constraining the problem further into an epsilon-constrained nJRRA problem, classic solution algorithms can be applied to solve the quadratically constrained quadratic program (QCQP). On top of this "basic model", we propose adding a decision to delay the resource allocation decisions up to a maximum initiation time when the incident duration is stochastic. To test the models, a quasi-dynamic evaluation program with a given incident duration distribution is constructed using discretized time steps and discrete distributions. Five different demand patterns and four different disruption duration distributions (20 combinations) are tested on a toy transit network. The results show that the two models outperform benchmark strategies such as using only line level adjustment or only bus bridging. They also highlight conditions when delaying the decision is preferred.

翻译：中断后的快速恢复对公共交通系统的可靠性至关重要。本研究提出了一种新尝试，以全面且分层次的方式解决公共交通中断缓解问题。我们构建了一个网络级策略选择优化模型，将其形式化为联合路由与资源分配问题。通过进一步将该问题约束为ε约束的联合路由与资源分配问题，可应用经典求解算法来解决二次约束二次规划。在此"基础模型"之上，我们提出增加一项决策——在事件持续时间随机的情况下，可将资源分配决策延迟至最大启动时间。为测试模型，我们利用离散时间步长和离散分布构建了一个准动态评估程序，其中包含给定的事件持续时间分布。在模拟公交网络上测试了五种不同的需求模式和四种不同的中断持续时间分布（共20种组合）。结果表明，这两个模型优于仅使用线路级调整或仅使用公交接驳等基准策略，同时也揭示了优先选择延迟决策的条件。