Location Optimization And Operation Scheduling Of Public Transportation Hubs

With the development of urbanization process, the urban transit system has been developing rapidly. Public transportation hubs are the physical carriers of urban transit system. Whether the layout and operational efficiency of the hubs are reasonable directly influences the connection of the whole network. Thus, according to the connection of hubs, this paper focuses on location optimization and operation scheduling of public transportation hubs. The main contents of this paper are as follows: (1) The location optimization of public transportation hubs. Proper location of hubs is the basis to achieve its function. The transport efficiency of the whole network should be improved at the lowest consumption. As the optimization process of hubs location is related to many factors, it is difficult to get a reasonable solution if there are a large number of candidate hubs. To improve the accuracy of the solution and reduce the computational time, a candidate hub location model based on fascination is presented. Then, on the basis of candidate hubs model, an optimization model of a single hub location and of multi-hub location are also proposed. As the multi-hub location optimization model is a multi-subjective optimization model, a multi-subjective genetic algorithm based on a ranking method is adopted to solve the multi-hub location optimization model. The model and the algorithm are examined by the data of Dalian city and the results indicate that the candidate hubs gained by the candidate hubs model are in accordance with the actual situation of Dalian city. And the proposed multi-hub location model is more effective than the single hub location model for proving more transit service.(2) The timetable optimization of public transportation hubs. Public transportation hubs operation is the main work of transit operator. Timetable optimization is the most important part of the operation, which directly or indirectly determines the vehicle scheduling, driver arrangement, etc. Therefore, according to the operation features of transit routes in hubs, this paper considers the route which plays the strongest effect on the waiting time in hubs as the basic line to achieve the maximum synchronization of other routes with the basic line. In order to reduce the randomness effect of arrival time of transit vehicles, some slack time is proposed. Thus, the timetable model of the multi-hub is also proposed based on the timetable model of the single hub. SCE-UA, an evolution algorithm, is used to solve this model. Finally, the model and the algorithm are examined by simulation analysis. The results demonstrate that the effect of multi-hub timealbe optimization is better than that of each hub timetable optimization and the robustness of the optimization model with the slack time is better than that of the optimization mode without the slack time.(3) The research on dynamic control strategies of public transportation hubs. The running environment of transit vehicle is very complicated and often affected by many stochastic factors. The influence can be weakened by taking effective measures to restore the normal operation of transit routes in hubs. Due to the real-time feature of dynamic dispatching, the prediction accuracy of transit vehicle running time prediction model can be improved with a forgetting factor. Considering that the condition of transit vehicles is dynamic and the accurate prediction of optimal slack time can ensure a good convergence of transfer routes and reduce the waiting time of passengers, the slack time prediction model is also presented. And on the basis of real-time vehicles operational information, the features of dynamic control strategies based on the hubs are analyzed, and a dynamic dispatching model aiming at minimizing the waiting time of passengers is proposed. Since the dynamic dispatching model is a complicated problem, a genetic algorithm is also used to solve the model. Then the model and the algorithm are examined with data of Dalian city.Finally, a summary is given and some contributions are discussed.