Optimization Of Transit Network Design Based On Immune Genetic Algorithm

Urban transportation is the tie for the resident to engage in kinds of activities in dailylife, it plays a great role in the economy and urban development. With the development of the urban construction, urban population grows fast, which makes the demand of urban traffic increase more rapidly. Because of the unbalance between the speed of transportation facilities construction and traffic demand increasement, the situation of urban transportation is deteriorating day by day, which has become a bottleneck restricting urban development. The objective of optimizing transit network is to make good use of the existing transport resources and improve the effectiveness of transit system by optimizing the transit network layout. Obviously, transit optimization is an effective measure that cost less and easier to implement.Based on the demand of transit network design, the research of transit network design in this thesis is intending to make the transit network better and improve the efficiency of the public transportation.Model and optimization algorithm is the crucial part of transit network design problem, after series of summary and analysis of the research in this field, this thesis proposes a model to minimize the total travel time of passengers, with route length, non-linear coefficient, transfer coefficient and load factor as constrains. Routes will be generated according to the shortest path and k-shortest path algorithm. Improved Immune Genetic Algorithm is used to optimize the network, and the method is tested by an example network;Finally, based on the OD demand matrix that is surveyed from Dandong city, this thesis analyzes the trip characteristics and the status of public traffic in Dandong, and modifies the bus routes according to the trip distribution which is done by TransCAD.