Abstract: Considering that the existing model doesn't take into account the transit network and frequency synchronous optimization and that optimization algorithm is inefficient, a mixed integer programming model is designed to optimize transit network and corresponding frequency with the aim of minimizing travel time. To increase the efficiency of the algorithm, the structure of public transportation network is evaluated based on setting the lower bound of transfer. If the transfer ratio is greater than the set lower bound, the frequency and objective function will not be calculated, which can reduce the computation caused by unfeasible solutions. A case is tested by the proposed model and algorithm, showing that the method can obtain the transit network and frequency simultaneously. Finally, the influence on computation time and optimization results are analyzed by different values of lower bound. The results show that the optimization results are the same and more than 40% of the computation time can be saved at most with the lower bound ranging from 1 to 0.4. However, when the lower bound is less than 0.4, the optimized solution by this algorithm is not optimal, which suggests that setting reasonable values for lower bound for the proposed method can save the computation time significantly with reliable solution, when the model and algorithm are applied to design transit network.

Key words: urban traffic, simultaneous optimization, improved genetic algorithm, transit network and frequencies, transit planning