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Title: | OPTIMIZATION MODELS FOR RAIL TRANSIT RESILIENCE | Authors: | XU LEI | Keywords: | rail transit networks; resilience; railway disruption management; uncertainty; robust optimization; stochastic programming | Issue Date: | 19-Aug-2019 | Citation: | XU LEI (2019-08-19). OPTIMIZATION MODELS FOR RAIL TRANSIT RESILIENCE. ScholarBank@NUS Repository. | Abstract: | Rail transit is an essential public transportation system that can enable mass rapid mobility in highly populated cities. At the same time, rail transit is frequently vulnerable to disruptions which are uncertain in nature. Resilience has evolved as a critical concept for quantifying the ability of critical infrastructure to withstand a major disruption. In this thesis, we study the resilience of rail transit systems by means of three optimization paradigms. First, we focus on optimizing the system’ robustness against worst-case disruptions using two-stage robust mixed-integer linear programming models. Then, we propose a novel performance metric to quantify the disruption tolerance under uncertainty. This is used as the objective function of a distributionally robust optimization problem. The bus-bridging service design is then the focus of the third work. In this work, we formulate a two-stage stochastic programming model to optimize bus-aided recovery for rail transit disruptions under uncertainty. | URI: | https://scholarbank.nus.edu.sg/handle/10635/165487 |
Appears in Collections: | Ph.D Theses (Open) |
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