Optimization Of Public Transportation Dispatch Based On Complex Complex Network

With the development of intelligent public transport in recent years,the service capacity of public transport system has been significantly enhanced.A large number of data have been generated,which can provide reference for public transport planning and decision-making of management departments.However,these data are not fully utilized,and the association between them is often ignored in the process of using.It often makes the analysis and optimization of public transportation system fall into local problems rather than the optimization of the whole public transportation system.For example,in the problem of public transportation scheduling optimization,public transportation settings will change in the process of searching the optimal solution.However,the passenger flow model obtained from historical data can not adapt to the change of public transport settings,resulting in optimization target calculation error and other problems.To solve this problem,the complex network model of public transportation is established in this thesis,which organizes the multi-source data of public transportation effectively.Each public transport element is described through this model,and the passenger flow is simulated and redistributed in the process of public transport optimization.On this basis,the optimization of public transportation scheduling is carried out by genetic algorithm.The main work of this thesis is as follows:(1)A complex public transport network model is proposed.Public transportation system is a typical complex network problem,which has significant characteristics of time and space.The network model can effectively organize the public transportation data,mine the public transportation information,and optimize the evolution simulation of the public transportation network.(2)An optimization algorithm of public transportation network is designed.Based on the complex network model of public transport and the principle of genetic algorithm,this algorithm focuses on the residents' choice behavior of public transport and the redistribution of passenger flow in the process of network optimization.The algorithm takes the bus operation cost as the constraint and the travel time of citizens as the optimization objective.Moreover,the algorithm simulates the OD weight of public transport travel,the selection of starting and ending stations,the transfer of public transport lines and other factors.The purpose of the algorithm is to improve the efficiency of public transport on the premise of controlling the existing public transport capacity.(3)The research content of this thesis is verified by an example.Combined with Qingdao public transport data,the role of multi-source public transport data in public transport optimization is discussed.based on the above model and algorithm,the data processing and model building are carried out.Qingdao public transportation network scheduling is optimized by this algorithm,and an effective scheme is proposed.