Please wait a minute...
文章检索
复杂系统与复杂性科学  2014, Vol. 11 Issue (4): 10-18    DOI: 10.13306/j.1672-3813.2014.04.003
  本期目录 | 过刊浏览 | 高级检索 |
基于复杂网络的危险品运输网络抗毁性仿真
种鹏云1, 帅斌1, 尹惠2
1.西南交通大学交通运输与物流学院,成都 610031;
2.中国水电顾问集团昆明勘测设计研究院,昆明 650051
Invulnerability Simulation Analysis of Hazardous Materials Transportation Network Based on Complex Network
CHONG Pengyun1, SHUAI Bin1, YIN Hui2
1. School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China;
2. Kunming Hydroelectric Investigation Design and Research Institute China Hydropower Engineering Consulting Eroup Corporation, Kunming 650051, China
全文: PDF(1464 KB)  
输出: BibTeX | EndNote (RIS)      
摘要 通过构建危险品运输超网络模型,分析了网络之间的相互作用和影响,继而建立了危险品运输网络模型生成方式;通过引入危险品运输网络“最短路径”、“平均最小风险路径距离”和“网络最大连通子图”概念,提出了“网络风险效率”和“最大连通度”抗毁性测度模型;根据网络流量特性,构建了危险品运输网络介数模型。以危险品运输网络为例进行仿真,仿真结果表明:危险品运输网络抗毁性表现为对随机攻击的鲁棒性和蓄意攻击的脆弱性,抗毁性更接近于无标度网络;其抗毁性是由少数节点和边维系的,且网络对节点攻击的抗毁性低于对边攻击的;网络最大连通度性能优于网络风险效率,适当增加系统冗余性可提高网络抗毁性。
服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章
种鹏云
帅斌
尹惠
关键词 复杂网络危险品运输网络抗毁性介数超网络    
Abstract:It analyzed the interaction and impact between the networks by establishing the supernetworks of HMTN, and then the generating method of HMTN was established. It defined the concept of “the shortest path of HMTN”, “the average risk-path distance” and “the maximal connected subgraph”, proposed the “efficiency of network risk” and “maximal connected degree” as the measurement indexes of invulnerability model of HMTN. It established betweenness centrality model of HMTN according to its flow characteristic. Then the performance of invulnerability of HMTN was respectively researched. The simulation results show that: the invulnerability of HMTN is closer to the scale-free network which is robustness to random attack and vulnerability to deliberate attack; the invulnerability of HMTN is maintained by a small number of nodes and edges and the invulnerability of edge is higher than the node’s; the maximal connected degree of HMTN outperforms the efficiency of network risk and increase the redundancy of system appropriately can improve the invulnerability of HMTN.
Key wordscomplex network    hazardous materials transportation network    invulnerability    betweenness centrality    supernetworks
收稿日期: 2013-05-24      出版日期: 2026-06-22
基金资助:国家自然科学基金(71173177)
作者简介: 种鹏云(1988-),男,陕西渭南人,博士研究生,主要研究方向为复杂网络抗毁性、突发事件应急管理和城市公共安全网络规划。
引用本文:   
种鹏云, 帅斌, 尹惠. 基于复杂网络的危险品运输网络抗毁性仿真[J]. 复杂系统与复杂性科学, 2014, 11(4): 10-18.
CHONG Pengyun, SHUAI Bin, YIN Hui. Invulnerability Simulation Analysis of Hazardous Materials Transportation Network Based on Complex Network[J]. Complex Systems and Complexity Science, 2014, 11(4): 10-18.
链接本文:  
https://fzkx.qdu.edu.cn/CN/10.13306/j.1672-3813.2014.04.003      或      https://fzkx.qdu.edu.cn/CN/Y2014/V11/I4/10
[1] 吴宗之, 孙猛. 200起危险化学品公路运输事故的统计分析及对策研究[J]. 中国安全生产科学技术,2006,2(2):3-8.
Wu Zongzhi, Sun Meng. Statistic analysis and countermeasure study on 200 road transportation accidents of dangerous chemicals[J]. Journal of Safety Science and Technology, 2006,2(2):3-8.
[2] Kara B Y, Verter V. Designing a road network for hazardous materials transportation[J]. Transportation Science, 2004, 38(2):188-196.
[3] Erkut E, Alp O. Designing a road network for hazardous materials shipments[J]. Computers & Operations Research, 2007, 34(5):1389-1405.
[4] Erkut E, Gzara F. Solving the hazmat transport network design problem[J]. Computers & Operations Research, 2008, 35(7):2234-2247.
[5] Verter V, Kara B Y. A path-based approach for hazmat transport network design[J]. Management Science, 2008, 54(1):29-40.
[6] Gao Q, Yan Q, Luo Y, et al. Designing a road network for hazardous materials transportation with fuzzy parameters based on optimum communication steiner tree[C]//International Conference on Transportation Engineering 2009, ASCE.Chengdu, 2009:3730-3735.
[7] Bianco L, Caramia M, Giordani S. A bilevel flow model for hazmat transportation network design[J]. Transportation Research Part C:Emerging Technologies, 2009, 17(2):175-196.
[8] 宋杰珍,丁以中,孟林丽. 基于双层规划的危险品运输网络设计[J]. 上海海事大学学报, 2006,27(2):56-59.
Song Jiezhen, Ding Yizhong, Meng Linli. Hazardous material transportation network design based on bi-level programming[J]. Journal of Shanghai Maritime University, 2006,27(2):56-59.
[9] 储庆中, 张家应, 谢之权. 基于双层规划的危险品道路运输网络设计[J]. 重庆交通大学学报(自然科学版), 2010,29(4):597-603.
Chu Qingzhong, Zhang Jiaying, Xie Zhiquan. Road network design for hazardous materials transportation based on bi-level programming[J]. Journal of Chongqing Jiaotong University(Natural Sciences), 2010,29(4):597-603.
[10] Ellison R J, Fisher D A, Linger R C, et al. Survivable network systems:an emerging discipline[R]. Camegie-mellon Univ pittsburgh P A software Engineering Inst,1997.
[11] Albert R, Jeong H, Barabási A L. Error and attack tolerance of complex networks[J]. Nature, 2000, 406(6794):378-382.
[12] Jeong H, Mason S P, Barabási A L, et al. Lethality and centrality in protein networks[J]. Nature, 2001, 411(6833):41-42.
[13] Newman M E J, Forrest S, Balthrop J. Email networks and the spread of computer viruses[J]. Physical Review E, 2002, 66(3):35-101.
[14] 李勇, 邓宏钟, 吴俊, 等. 基于级联失效的复杂保障网络抗毁性仿真分析[J]. 计算机应用研究. 2008, 25(11):3451-3454.
Li Yong, Deng Hongzhong,Wu Jun, et al. Invulnerability simulation analysis of complex logistics networks based on cascading failure[J]. Application Research of Computers, 2008, 25(11):3451-3454.
[15] 王伟,刘军,李海鹰,等. 铁路网抗毁性分析[J]. 铁道学报. 2010, 32(4):18-22.
Wang Wei, Liu Jun, Li Haiying, et al. Survivability analysis of railway network[J]. Journal of the China Railway Society, 2010, 32(4):18-22.
[16] 汪涛,吴琳丽.基于复杂网络的城市公交网络抗毁性分析[J]. 计算机应用研究. 2010, 27(11):4084-4086.
Wang Tao,Wu Linli. Research on invulnerability of urban transit network based on complex network[J]. Application Research of Computers, 2010, 27(11):4084-4086.
[17] 陈春霞. 基于复杂网络的应急物流网络抗毁性研究[J]. 计算机应用研究. 2012, 29(4):1260-1262.
Chen Chunxia. Study on invulnerability of emergency logistics network based on complex network[J]. Application Research of Computers, 2012, 29(4):1260-1262.
[18] 种鹏云,帅斌,陈钢铁. 恐怖袭击下危险品运输网络级联失效抗毁性建模与仿真[J]. 计算机应用研究. 2013,30(1):107-110.
Chong Pengyun, Shuai Bin, Chen Gangtie. Model and simulation on cascading failure survivability of hazardous materials transportation network under terrorist attack[J]. Application Research of Computers, 2013,30(1):107-110.
[19] 王众托, 王志平. 超网络初探[J]. 管理学报. 2008,5(1):1-8.
Wang Zhongtuo, Wang Zhiping. Elementary study of supernetworks[J]. Chinese Journal of Management, 2008,5(1):1-8.
[20] Correa J R, Schulz A S, Stier-Moses N E. Selfish routing in capacitated networks[J]. Mathematics of Operations Research, 2004, 29(4):961-976.
[21] Nagurney A, Dong J. Supernetworks:decision-making for the information age[M]. Cheltenham:Edward Elgar Publishing, 2002.
[22] Holme P, Kim B J, Yoon C N, et al. Attack vulnerability of complex networks[J]. Physical Review E, 2002, 65(5):1-14.
[1] 岳芳, 张涵, 樊茂瑞, 戴文慧, 郭剑锋. 开放式交互平台知识协同中的群体观点演化模型与实证[J]. 复杂系统与复杂性科学, 2026, 23(2): 8-18.
[2] 孙艳琴, 吴怀宇, 陈志环. 异维异构多重边复杂网络的广义外同步控制[J]. 复杂系统与复杂性科学, 2026, 23(2): 34-40.
[3] 于海波, 高彦丽, 陈世明, 凤超. 异质耦合下铁路-经济多层网络鲁棒性分析[J]. 复杂系统与复杂性科学, 2026, 23(2): 48-56.
[4] 聂廷远, 王艳伟, 聂晶晶, 刘鹏飞. 基于注意力机制和复杂网络的FPGA可布性预测[J]. 复杂系统与复杂性科学, 2026, 23(1): 53-59.
[5] 户佐安, 杨江浩, 邓锦程. 考虑多元变量的世界航空网络综合鲁棒性研究[J]. 复杂系统与复杂性科学, 2026, 23(1): 60-69.
[6] 孙小慧, 刘毅, 米玉梅, 吕凯. 韧性视角下城市地铁与常规公交网络关键站点及线路识别[J]. 复杂系统与复杂性科学, 2026, 23(1): 26-36.
[7] 牟奇锋, 李晓倩. 基于邻接矩阵的复杂网络演化融合迭代方法[J]. 复杂系统与复杂性科学, 2026, 23(1): 79-86.
[8] 孙文静, 余路粉, 潘文林, 蓝春江. 基于节点影响因子和贡献因子的复杂网络重要节点识别[J]. 复杂系统与复杂性科学, 2026, 23(1): 87-95.
[9] 卢新彪, 刘泽诚, 陈贵允, 杨铁流, 高兴. 基于图卷积网络的复杂网络能控性提升方法[J]. 复杂系统与复杂性科学, 2025, 22(4): 24-28.
[10] 周青, 李依函, 陈文冲. “互联网+”企业创新生态系统网络演化分析[J]. 复杂系统与复杂性科学, 2025, 22(4): 1-7.
[11] 章浩淳, 寇博潇, 张泰杰, 唐智慧. 基于Granger Causality的滑坡机理网络客观权值确定方法[J]. 复杂系统与复杂性科学, 2025, 22(4): 63-70.
[12] 韩世翔, 闫光辉, 裴华艳. 复杂网络上双向免疫对传染病传播的影响[J]. 复杂系统与复杂性科学, 2025, 22(4): 55-62.
[13] 张琦, 汪小帆. 复杂网络观点动力学分析与干预若干研究进展[J]. 复杂系统与复杂性科学, 2025, 22(2): 31-44.
[14] 张明磊, 宋玉蓉, 曲鸿博. 基于图注意力机制的复杂网络关键节点识别[J]. 复杂系统与复杂性科学, 2025, 22(2): 113-119.
[15] 陶昭, 侯忠生. 复杂网络的无模型自适应牵制控制[J]. 复杂系统与复杂性科学, 2025, 22(2): 120-127.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed