Genetic Algorithm In Optmization Research Of Public Traffic Vehicles Scheduling

Urban public transport is an integral part of city life, which provides a basic guarantee for urban residents living normally, also promotes economic prosperity and development of the city. It is a very important support force to strengthen the rural-urban linkages. With the development of the national economy, China’s urbanization process is further accelerated, and the living standards have been improved significantly, which increases the urban road traffic load, there has been road traffic congestion, frequent accidents, increasing environment and noise pollution and other’urban disease’. Clearly, urban traffic pressure is too saturated, which seriously affects the city’s economic development, and daily life of the residents, this problem is particularly prominent in the major cities. In order to ease the traffic pressure, many China’s major cities have launched a bus priority strategy. However, because of the vehicle scheduling plan is not that scientific, while the process of moving buses will be affected by various factors, such as road congestion, accidents, weather conditions, etc., it will not only affects the passenger waiting time, causing congestion inside of the bus, but also a waste of resources on public transport. So based on all those background it has been discussed, come up with a scientific and reasonable bus scheduling scheme is an effective way to release the existing urban traffic pressure, with speedily significance.Firstly, the theory of public transportation vehicle scheduling systems and genetic algorithms have been studied, including the basic principle of public transport vehicle scheduling system, influencing factors and scheduling optimization method. And also the principles, terminology and key steps of genetic algorithm has been analyzed, especially focuses on n the cost of bus scheduling system constituted to provide basic theoretical support for the construction of vehicle scheduling optimization model, as well as the text of the model solution to establish a foundation.Secondly based on the characteristics of buses scheduling, considering the interest of the bus company and the benefits of passengers who use the public transportation, a vehicle scheduling optimization model has been constructed. In the model, the bus company operating costs and passenger travel costs has been used as the objective, while the departure time of buses as a decision variable intervals, taking into account the actual load factor in buses, the adjacent maximum and minimum headway between trains, as a model of constraints. A improved genetic algorithm has been introduced to solve the model and aimed to find a good solution.Lastly based on the statistic of Wuxi Public transport company, by designing of the genetic operators, selecting the relevant genetic parameters, several simulation experiments has been conducted with many results of the vehicle scheduling optimization in different periods, i.e. the dispatching schedule. The result of the model could reduce the passengers’waiting time for the bus, but also improve the service quality of the bus company, achieving the intelligent dispatching of the public transportation system.