交通运输系统工程与信息 ›› 2015, Vol. 15 ›› Issue (2): 109-115.

• 系统工程理论与方法 • 上一篇    下一篇

突发状况下危险品运输网络鲁棒性建模和仿真

胡鹏,帅斌*,狄兆华   

  1. 西南交通大学交通运输与物流学院,成都610031
  • 收稿日期:2014-08-07 修回日期:2014-10-22 出版日期:2015-04-25 发布日期:2015-04-27
  • 作者简介:胡鹏(1989-),男,贵州遵义人,博士生.
  • 基金资助:

    国家自然科学基金(71173177);四川省科技厅苗子工程资助项目(2014-013).

Model and Simulation for the Robustness of Hazardous Goods Transportation Network under Emergency

HU Peng,SHUAI Bin,DI Zhao-hua   

  1. College of Transportation & Logistics, Southwest Jiaotong University, Chengdu 610031, China
  • Received:2014-08-07 Revised:2014-10-22 Online:2015-04-25 Published:2015-04-27

摘要:

由于突发状况,危险品运输受到影响或威胁,其后果是致命的.因此针对危险品运输网络进行鲁棒性分析,以利于网络的设计和选择.本文基于自然渗流现象与复杂网络的渗流理论相结合,对危险品运输网络的鲁棒性进行定义,并从整体性角度,基于图论提出网络连通率;从微观细节的角度,提出渗流节点数、渗流失效率、节点承载力、渗流阻尼参数.从定义和实际出发,提出假设条件,建立模型,设定仿真场景.最后,根据仿真流程图,使用Matlab 仿真.根据仿真结果,定性定量分析不同节点度节点突发状况和不同节点承载系数对危险品运输网络节点失效渗流鲁棒性的影响.

关键词: 公路运输, 鲁棒性, 仿真模型, 危险品运输网络, 突发状况, 渗流

Abstract:

Under emergency circumstances, dangerous goods transport is affected, and the consequences are fatal. Therefore, the robustness of hazardous goods transportation network is analyzed for facilitating the design of that network. In this paper, based on natural seepage phenomenon and the percolation theory of complex networks, the robustness of dangerous goods transportation network is defined, and then, from the perspective of wholeness, network connectivity rate is proposed based on graph theory. From the perspective of micro details, they are put forward that the number of percolation nodes, the failure rate of percolation, node capacity, and the percolation damping parameter. Starting from these definitions and the actuality, models are established and the simulation scenario with assumptions is set up. Finally, according to the simulation flow chart, Matlab simulation is adopted. According to the simulation results, we apply qualitative and quantitative analysis to acquiring the influence of the percolation robustness of hazardous goods transportation network for nodes failure with the different node- degree and node- capacity coefficient in emergency conditions.

Key words: highway transportation, robustness, simulation model, hazardous goods transportation network, emergency, percolation

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