This paper focuses on an urban transit line which connects several residential areas and a workplace during the morning rush hours. The congestion is represented by some passengers who must wait for an extended duration and board the next or the third departure vehicles. This paper divides the time horizon equally into several small periods to measure the dynamic passenger demands. Under period-dependent demand conditions, a biobjective optimization model is developed to determine the departure times of transit vehicles at the start station with strict capacity constraints, in which a heuristic algorithm based on intelligent search and local improvement is designed to solve the model. The developed model can address the case in which more than two passengers arrive at a station simultaneously during one same period and calculate the number of boarded passengers. Finally, the model and algorithm have been successfully verified by a numerical example.