基于元启发式解决铁路交通网络中的车辆流量管理问题  

Meta-heuristic-based solutions for vehicle flow management in railway traffic networks

作　　者：张怡[1] 史歌[1] 左静[2] Zhang Yi;Shi Ge;Zuo Jing(School of Transportation,Xi'an Railway Polytechnic,Xi'an,Shaanxi 710000,China;School of Automation and ElectricalEngineering,Lanzhou Jiaotong University,Lanzhou,Gansu 730070,China)

机构地区：[1]西安铁路职业技术学院交通运输学院,陕西西安710000 [2]兰州交通大学自动化与电气工程学院,甘肃兰州730070

出　　处：《现代科学仪器》2024年第1期141-146,共6页Modern Scientific Instruments

基　　金：陕西省“十四五”教育科学规划2022年度课题(编号:SGH22Y1646)。

摘　　要：铁路交通网络的设计在铁路交通规划过程中起着关键作用,但目前铁路交通网络的车辆流量管理问题在铁路交通中得到了极大的关注。因此,提出启发式的多层铁路交通网络协同进化模型,其下层网络和上层网络与增长相关并相互刺激。首先使用相对邻接图和加布里埃尔图分别模拟了高速铁路和普通铁路网络的结构。研究结果表明,当增加特定数量的节点时,扩大后的网络与最初的下层网络之间的车辆流量具有最低值。随着Θ的增加,Ψ从大约2.5增加到3.4,进一步缓和铁路交通网络中车流量管理问题。研究成果可为铁路交通网络拓扑特征的分析和对车辆流量管理提供参考依据。The design of railway transportation network plays a key role in the process of railway transportation planning,but the vehicle flow management of railway transportation network has received great attention in railway transportation.Therefore,a heuristic multi-layer railway transportation network co evolution model is proposed,where the lower and upper layers of the network are related to growth and mutually stimulate each other.Firstly,the structures of high-speed railway and ordinary railway networks were simulated using relative adjacency diagrams and Gabriel diagrams,respectively.The research results indicate that when a specific number of nodes are added,the vehicle traffic between the expanded network and the initial lower level network has the lowest value.along withΘThe increase in,ΨIncreasing from approximately 2.5 to 3.4 further alleviates traffic flow management issues in railway transportation networks.The research results can provide reference for the analysis of railway transportation network topology characteristics and vehicle flow management.

关 键 词：元启发式 铁路交通 车辆流量 管理 

分 类 号：U49[交通运输工程—交通运输规划与管理]