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Evacuation Route Planning Algorithm: Longer Route Preferential

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Advances in Neural Networks – ISNN 2009 (ISNN 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5551))

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Abstract

Given a transportation network with capacity constraints, the initial occupancies and the destination nodes, evacuation route planning generates a set of evacuation routes and a schedule for the movement of people and vehicles along these routes, such that the evacuation is completed in the shortest possible time. This is a critical step in disaster emergency management and homeland defense preparation. In order to avoid the large storage and calculation costs brought by the time-expended-graph for transforming dynamic network flow problem to static network flow problem, the heuristic algorithm of the Capacity Constrained Route Planner (CCRP) is researched. One defect of the original CCRP algorithm is studied carefully and the new algorithm with longer route preferential is proposed to improve it. The result of the experiment shows the feasibility of the algorithm.

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References

  1. ESRI: GIS for Homeland Security. An ESRI white paper (2001)

    Google Scholar 

  2. The Homeland Security Council.: Planning Scenarios, Executive Summaries, Created for Use in National, Federal, State, and Local Homeland Security Preparedness Activities (2004)

    Google Scholar 

  3. Brown, S.: Building America’s Anti-Terror Machine: How Infotech Can Combat Homeland Insecurity. J. Fortune, 99–104 (2002)

    Google Scholar 

  4. The Volpe National Transportation Systems Center: Improving Regional Transportation Planning for Catastrophic Events (FHWA). Volpe Center Highlights, 1–3 (2002)

    Google Scholar 

  5. Hamacher, H.W., Tjandra, A.: Mathematical modeling of evacuation problems: State of the Art. J. Pedestrian and Evacuation Dynamics, 227–266 (2001)

    Google Scholar 

  6. Chalmet, L., Franis, R., Saunders, P.: Network Model for Building Evacuation. J. Management Science. 28, 86–105 (1982)

    Article  Google Scholar 

  7. Francis, R., Chalmet, L.: A Negative Exponential Solution To An Evacuation Problem. Research Report. National Bureau of Standards. Center for Fire Research (1984)

    Google Scholar 

  8. Hoppe, B., Tardos, E.: Polynomial Time Algorithms for Some Evacuation Problems. In: Proceedings for the 5th Annual ACM-SIAM Symposium on Discrete Algorithms, pp. 433–441 (1994)

    Google Scholar 

  9. Akiva, M.B., et al.: Development of a Deployable Real-Time Dynamic Traffic Assignment System: DynaMIT and DynaMIT-P User’s Guide. Massachusetts Institute of Technology (2002)

    Google Scholar 

  10. Mahmassani, H., Sbayti, H., Zhou, X.: DYNASMART-P Version 1.0 User’s Guide. Maryland Transportation Initiative, University of Maryland (2004)

    Google Scholar 

  11. Lu, Q., George, B., Shekhar, S.: Capacity Constrained Routing Algorithms for Evacuation Planning: A Summary of Results. In: Bauzer Medeiros, C., Egenhofer, M.J., Bertino, E. (eds.) SSTD 2005. LNCS, vol. 3633, pp. 291–307. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  12. Ahuja, R.K., Magnanti, T.L., Orlin, J.B.: Network Flows: Theory, Algorithms, and Applications. Prentice-Hall, Englewood Cliffs (1993)

    MATH  Google Scholar 

  13. Ford, L.R., Fulkerson, D.R.: Flows in Network. Princeton University Press, Princeton (1962)

    MATH  Google Scholar 

  14. Kennington, J., Helgason, R.: Algorithm for Network Programming. John Wiley & Sons, Inc., New York (1980)

    MATH  Google Scholar 

  15. Frangioni, A., Manca, A.: A Computational Study of Cost Reoptimization for Min-Cost Flow Problems. J. Informs journal on computing, 61–70 (2006)

    Google Scholar 

  16. Theodoulou, G., Wolshon, B.: Alternative Methods to Increase the Effectiveness of Freeway Contraflow Evacuation. J. Technical Report Transportation Research Record. The Journal of Transportation Research Board 1865, 48–56 (2004)

    Article  Google Scholar 

  17. Jha, M., Moore, K., Pashaie, B.: Emergency Evacuation Planning with Microscopic Traffic Simulation. J. The Journal of Transportation Research Board 1886, 40–48 (2007)

    Article  Google Scholar 

  18. Lu, Q., Huang, Y., Shekhar, S.: Evacuation Planning: A Capacity Constrained Routing Approach. In: Chen, H., Miranda, R., Zeng, D.D., Demchak, C.C., Schroeder, J., Madhusudan, T. (eds.) ISI 2003. LNCS, vol. 2665, pp. 111–125. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  19. Kim, S., George, B., Shekhar, S.: Evacuation Route Planning: Scalable Heuristics. In: Proceedings of the 15th International Symposium on Advances in Geographic Information Systems. ACM GIS (2007)

    Google Scholar 

  20. Hoogendoom, S., Bovy, P.: State of the Art of Vehicular Traffic Flow Modeling. J. Proceedings of the Institution of Mechanical Engineers, Part 1: Journal of Systems and Control Engineering 215, 283–303 (2001)

    Article  Google Scholar 

  21. Klingman, D., Napier, A., Stutz, J.: NETGEN: A Program for Generating Large Scale Capacitated Assignment, Transportation, and Minimum Cost Flow Network Problems. J. Management Science 20, 814–821 (1974)

    Article  MATH  Google Scholar 

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Author information

Authors and Affiliations

  1. Hubei Key Laboratory of Digital Valley Science and Technology, Huazhong University of Science & Technology, Wuhan, 430074, China

    Maimai Zeng & Cheng Wang

Authors
  1. Maimai Zeng
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  2. Cheng Wang
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Editor information

Editors and Affiliations

  1. Departamento de Control Automático, CINVESTAV-IPN, A.P. 14-740, Av.IPN 2508, 07360, México D.F., México

    Wen Yu

  2. Deptartment of Electrical and Computer Engineering, Stevens Institute of Technology, NJ 07030, Hoboken, USA

    Haibo He

  3. Dept. of Electrical and Computer Engineering, South Dakota School of Mines & Technology, 501 E. St. Joseph Street, Rapid City, SD 57701, USA

    Nian Zhang

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© 2009 Springer-Verlag Berlin Heidelberg

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Zeng, M., Wang, C. (2009). Evacuation Route Planning Algorithm: Longer Route Preferential. In: Yu, W., He, H., Zhang, N. (eds) Advances in Neural Networks – ISNN 2009. ISNN 2009. Lecture Notes in Computer Science, vol 5551. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01507-6_119

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  • DOI: https://doi.org/10.1007/978-3-642-01507-6_119

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01506-9

  • Online ISBN: 978-3-642-01507-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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