Frequency Optimization In Public Transportation Systems Of Medium-small Cities

With the rapid development of social economy in our country, the size of smaller cities expands unceasingly, the contradiction of urban traffic supply and demand is becoming more and more seriously. The government and traffic management department of each smaller city has realized that: ―developing public transportation is the strategic choice to improve the city traffic‖ and ―solving the problem of the city traffic must develop the city bus priority‖. The bus line network is the foundation of the whole city bus system, the bus frequency determines the frequency of whole network and influences the service quality of operators and economic benefits directly. So, the optimization of bus frequency is the key whether the operation is successful. Therefore, in the development process of smaller cities, study on the problem of city bus system frequency optimization is benefit to break the bottleneck of the bus system development, improve the attractiveness and competitiveness of smaller cities, guide people to choose the bus to travel and promote the healthy development of smaller city bus system.This paper based on analyzing and studying the problem of domestic and foreign cities bus frequency optimization, then introduced the influence factors of smaller city bus frequency, and according to the actual situation of Linhe district of Baiyanzhuo’er for analyzing. On the basic of the model of Héctor Martínez and Antonio Mauttone(2014), under the condition of maximum capacity of bus stops and the limited size of the city bus fleet, building the optimization model which aimed at the minimum of the total travel time of passenger and the total operating cost of bus company. Verified the correctness of the bus frequency optimization model which this paper built by small scale data. Then, design a kind of an improved genetic algorithm to solve, optimized the bus line frequency of Linhe district of Baiyanzhuo’er. The optimization result shows the accuracy of the model which this paper built and effectiveness of the algorithm further.