Stochastic optimization model and solution algorithm for robust double-track train-timetabling problem

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 BeijingShanghai high-speed rail corridor in China.