Models And Algorithms Of Urban Public Transportation System

Preferential development of urban public transportation system is a universally accepted approach of solving urban traffic problem. Recently, intelligent public transportation system has become the important development trend of public transportation field. Based on the project background of public transportation system in Dalian city, the applications on ant colony optimization algorithm, support vector machine, SCE-UA algorithm, etc in the planning and the operation of urban public transportation system, are studied. Since urban public transportation system is a giant system, the corresponding models and strategies are very complex. In this dissertation, the parallel intelligent algorithms running in PC cluster are adoped to improve the optimization quality and speed. The major contents and research progress are as follows:1) Bus network is the basis of urban public transportation. The rationality of the bus network, therefore, directly influences the travel time and transfer rate of passengers, and the overall running cost of the transport systems. This dissertation presents an optimization model for bus network design, which aims to maximize the number of direct travelers per unit length, i.e. direct traveler density, subject to route length and non-linear rate constraints. Ant colony optimization (ACO), a new evolution algorithm, is used to solve the model. To improve the efficiency of the method, two improved strategies are proposed: 1) develops a new strategy to update the increased pheromone, called Ant-Weight, which considering the global and local information; 2) uses parallelization strategies of ACO improve the calculation time and the quality of the optimization. The data of Dalian city in China are used to test the model and the algorithm. The results show that compared with the preseng transit network the optimized one is more effective and efficient. They also reveal that the ANT-Weight strategy and coarse-grain strategy are effective.2) The optimization of the frequencies is the key of the operation plan, which determine the situation of the running schedule, vehicle adjustment and driver assignment. Considering the interactions between the operators (the demand) and the user (the supply), in this dissertation, a bi-level programming model for the bus frequencies design in the given network is presented. In the bi-level model, the upper-level is the leader and optimizes the bus frequencies by SCE-UA. The lower-level is the follower and its objective is to assign transit trips to the network based on travel strategy and the optimal frequencies. Finally the model and the algorithms are illustrated with the bus network in the city of Dalian in China. The results show that the model can effectively save the total cost of the operators and users...