Research On Key Node Identification And Robustness Optimization Of Urban Rail Transit Network

At present,many cities’ rail transit has been operated in a network,and the share of passenger flow in urban public travel has gradually increased.Scientific and reasonable planning is the key to ensure the stable operation of the urban rail transit system,and the mining of the inherent characteristics of the network is the basis of scientific planning.In this paper,the urban rail transit network is taken as the research object,from the perspective of complex network system analysis,combined with the cross-sectional passenger flow distribution theory,the basic nature,key nodes and robustness of the urban rail transit network are studied in order to Constructing an algorithm and a robust optimization model suitable for identifying key nodes of the urban rail transit network are of great significance for optimizing the layout of the urban rail network and improving the satisfaction of residents in public travel.This includes:(1)Modeling and mining of urban rail transit network.In this paper,considering the impact of passenger flow on the overall network of the urban rail network,combined with the relevant theory of passenger flow allocation,based on the L model method and the H model method,the urban rail transit basic road network passenger flow service network is constructed respectively.By analyzing the network measurement,Chongqing Rail The traffic is scale-free from the basic road network level to the passenger flow service network level,and the connectivity between the stations in the network is poor and has greater vulnerability;(2)Identification algorithm of key nodes in urban rail network.In order to accurately and efficiently identify the criticality of the nodes in the urban rail transit network,this paper improves the defect of the "Equalized Jump" in the Page Rank algorithm,and considers the impact of the station failure on other stations,respectively,based on the urban rail transit foundation Road network and passenger flow service network have constructed DSPGA and VSPGA key node identification algorithms.Through the four indicators of the global efficiency of the network constructed from the perspective of node deletion,the reduction rate of network connectivity,the importance of propagation constructed from the perspective of virus propagation,and the Kendall Rank correlation coefficient,the DSPGA and VSPGA are compared to the other four algorithms for urban rail The basic road network and service network of transportation have better accuracy and applicability;(3)Research on the robust optimization model of urban rail network.By deliberately attacking the urban rail transit basic road network and passenger flow service network in five different ways,it is found that the Chongqing rail transit network exhibits poor robustness when facing deliberate attacks,especially in DSPGA/VSPGA key nodes Under the order of deliberate attacks.It further proves the scale-free nature of Chongqing rail transit network and the superiority of DSPGA/VSPGA.It also shows that the criticality of nodes in Chongqing rail network is quite different.In order to improve the robustness of the urban rail transit network,this paper proposes a network robust optimization model under cost control.The combined optimization model is solved by a tabu search method combined with a complex network,and a specific optimized link combination is proposed.Related optimization suggestions.The research results of the thesis can provide reference for decision-making departments such as the planning,construction and operation management of urban rail transit.