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Disruption Management in Urban Rail Transit System: A Simulation Based Optimization Approach
Abstract
The process of disruption management in rail transit systems faces challenging issues such as the unpredictable occurrence time, the consequences and the uncertain duration of disturbance or recovery time. The objective of this chapter is to adopt a discrete-event object-oriented simulation system, which applies the optimization algorithms in order to compensate the system performance after disruption. A line blockage disruption is investigated. The uncertainty associated with blockage recovery time is considered with several probabilistic scenarios. The disruption management model presented here combines short-turning and station-skipping control strategies with the objective to decrease the average passengers' waiting time. A variable neighborhood search (VNS) algorithm is proposed to minimize the average waiting time. The computational experiments on real instances derived from Tehran Metropolitan Railway are applied in the proposed model and the advantages of the implementing the optimized single and combined short-turning and stop-skipping strategies are listed.
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