Print Email Facebook Twitter Resilience assessment of railway networks Title Resilience assessment of railway networks: Combining infrastructure restoration and transport management Author Bešinović, Nikola (TU Delft Transport and Planning) Nassar, R. (Student TU Delft) Szymula, Christopher (Technische Universität Dresden) Date 2022 Abstract During railways operations, unplanned events might occur which can result in rail traffic being heavily impacted. The paper proposes a passenger-centred resilience assessment for disruption scenarios which consist of multiple simultaneous disruptions. It combines train traffic operations, passenger flows and network restoration. To evaluate resilience, an optimization-based approach has been developed for solving the new infrastructure restoration and transport management (IRTM) problem. Additionally, this approach develops mitigation plans for the best infrastructure restoration and traffic recovery and it captures the time-dependent transport network performance during disruptions. The approach is general with respect to types of disruptions, and can be applied for evaluation against short disruptions (1–2 h) as well as more substantial ones (multiple days or weeks). The performance of the proposed approach has been demonstrated on a Dutch railway network. Furthermore, the resilience of the system is assessed against the critical infrastructure disruption scenarios in the network. This optimization-based approach shall enable decision makers to quantify accurately impacts of multiple disruptions by considering the created inconveniences to passengers in the railway operation due to these disruptions. Subject DisruptionsInfrastructureOptimizationPassengersRailwayResilienceTrains To reference this document use: http://resolver.tudelft.nl/uuid:0c4b1d4c-8825-477e-8943-645e92869678 DOI https://doi.org/10.1016/j.ress.2022.108538 ISSN 0951-8320 Source Reliability Engineering & System Safety, 224, 1-15 Part of collection Institutional Repository Document type journal article Rights © 2022 Nikola Bešinović, R. Nassar, Christopher Szymula Files PDF 1_s2.0_S0951832022001909_main.pdf 1.84 MB Close viewer /islandora/object/uuid:0c4b1d4c-8825-477e-8943-645e92869678/datastream/OBJ/view