When facing a surge in passenger demand especially during holidays, dispatchers have to adjust train operation organization for busy high-speed railway corridors. This paper is devoted to optimizing transport capacity considering the capacity pool and flexible train composition with time-dependent passenger demand to generate new timetables for both regular and additional trains. A bi-objective mixed integer programming model is formulated to minimize the waiting time of passengers and operation costs for capacity utilization. A local search technique is hybridized into an elitist heuristic algorithm based on NSGA-II to generate high-quality solutions. Two sets of numerical experiments are carried out based on a small-scale example and real-world data from the Wuhan-Guangzhou high-speed railway corridor to verify the effectiveness of the proposed methodology. The results show that (1) when considering time-dependent passenger demand, the satisfaction rate exceeds 90%; (2) when optimizing transport capacity, satisfaction is guaranteed while bringing reduction in operation costs.