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Stochastic Optimization Model and Solution Algorithm for Robust Double-Track Train-Timetabling Problem
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DOI：10.1109/TITS.2009.2030588.png)
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By considering various stochastic disturbances unfolding in a real-time dispatching environment, this paper develops a stochastic optimization formulation for incorporating segment travel-time uncertainty and dispatching policies into a medium-term train-timetabling process that aims to minimize the total trip time in a published timetable and reduce the expected schedule delay. Based on a heuristic sequential solution framework, this study decomposes the robust timetabling problem into a series of subproblems that optimize the slack-time allocation for individual trains. A number of illustrative examples are provided to demonstrate the proposed model and solution algorithms using data collected from a Beijing-Shanghai high-speed rail corridor in China.
Keyword:
Slack-time allocation
stochastic optimization
train scheduling
train timetabling
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